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Tumor-to-tumor metastasis is a rare phenomenon affecting the thyroid gland. Otherwise, it is not unusual for a neoplasm to be detected incidentally, without clinical symptoms. But what is exceptionally rare is that a malignant neoplasm debuts as an incidental finding in the form of a tumor-to-tumor metastasis. We contribute with the case of a previously healthy 41-year-old woman who presented an asymptomatic 39-mm-sized nodule on the left thyroid lobe in a routine health checkup. Ultrasound-guided fine needle aspiration cytology confirmed a papillary thyroid carcinoma. Because of the size, a total thyroidectomy was performed. In the surgical specimen, in addition to a classic papillary carcinoma with an extensive follicular pattern (pT2 pN0), a second component was identified, consisting of a clear cell population with immunostaining profile of renal origin. Subsequent studies found a 110-mm-sized left renal mass. A nephrectomy was performed and the pathological exam confirmed a renal cell carcinoma, pT2 pNX pM1, with metastasis also to the adrenal gland. To our knowledge, this is the first case described of this clinical presentation involving those two neoplasms. We present herein such an unusual clinical case along with a brief clinical and pathological review on tumor-to-tumor metastasis, with special emphasis on renal-to-thyroid ones.

Background There is still controversy whether full lung palpation is required for patients undergoing pulmonary metastasectomy. We aimed to compare pulmonary ipsilateral recurrence (IR) after video-assisted thoracic surgery (VATS) or open surgery. Methods A retrospective study of all patients who underwent surgery for colorectal cancer lung metastases between 2003 and 2012 was performed. IR rate was compared between the 2 groups after adjusting for a propensity score matching based on age, sex, disease-free interval, number of metastases, type of resection, presence of a cardiovascular risk factor, presence of a respiratory risk factor, as well as the interaction between the number of metastases and the disease-free interval. The propensity score was used for matched and weighted comparisons of VATS and open patients. Results A total of 211 patients underwent surgery for colorectal cancer lung metastases. Of these, 75 (35.5%) were performed via VATS and 136 (64.5%) via open surgery. Before matching, 118 (55.9%) were male and the median age at the time of metastases diagnosis was 61 (range, 49.8-72.2) years. Median disease free-interval was 20 (19.7 ± 28.3) months; 22 (21.6 ± 28.5) months in VATS and 19 (19.0 ± 28.3) months in open surgery. In total, 19 (25.3%) developed IR in VATS, and 39 (28.7%) in open surgery. Five-year overall survival was 53.1% (61.9% VATS; 49.2% open). In the matched sample, IR was 23.6% in VATS vs 26.2% in open surgery (95% confidence interval for risk reduction with VATS: –22.6% to 17.5%; P = .80). Conclusions No significant difference was observed in IR rates between VATS and open surgery in the treatment of colorectal cancer lung metastases.

Pre-eruptive intracoronary resorption is a rare condition mainly affecting pediatric patients. It is a radiographic finding in the dentin of the crown of an unerupted tooth just below the enamel-dentin junction. It is visualized in radiographs as a radiolucent coronal lesion of variable depth; it is well-defined and located in the dentin adjacent to the amelodentinal limit of an unerupted tooth. Historically, this lesion was misdiagnosed as caries and was misnamed pre-eruptive caries, when in reality they were pre-eruptive intracoronal resorptions. We present two rare cases of pre-eruptive intracoronary resorption in patients that needed radiographs for orthodontic purposes. The Oral & Maxillofacial Radiologist detected the existence of pre-eruptive intracoronary resorption in mandibular second premolars and mandibular second molar. These radiographic findings provided the clinician with the advantage of knowing this condition before teeth eruption, allowing for conservative treatment and periodic radiographic follow-up.

BACKGROUND: It has been proposed that neuromuscular or functional electrical stimulation may have effects on respiratory muscles through its systemic effects, similar to those produced by exercise training. However, its impact on the duration of invasive mechanical ventilation has not been adequately defined. We sought to evaluate the effect of neuromuscular or functional electrical stimulation on the duration of invasive mechanical ventilation in critically ill subjects. METHODS: We systematically searched 3 databases up to August 2019 (ie, CENTRAL, MEDLINE, and EMBASE) as well as other resources to identify randomized controlled trials (RCTs) that evaluated the effects of neuromuscular or functional electrical stimulation compared to usual care/rehabilitation or placebo of neuromuscular or functional electrical stimulation on the duration of invasive mechanical ventilation. RESULTS: After reviewing 1,200 single records, 12 RCTs (N = 530 subjects) fulfilled our eligibility criteria. Three studies included only subjects with COPD (n = 106 subjects), whereas the rest considered subjects with different diseases. The most frequently stimulated muscle group was the quadriceps. Neuromuscular or functional electrical stimulation may decrease the duration of invasive mechanical ventilation (mean difference = –2.68 d, 95% CI –4.35 to –1.02, I(2) = 50%, P = .002; 10 RCTs; low quality of evidence), and we are uncertain whether this effect may be more pronounced in subjects with COPD (mean difference = –2.90 d, 95% CI –4.58 to –1.23, I(2) = 9%, P < .001; 3 RCTs; very low quality of evidence). CONCLUSIONS: Neuromuscular or functional electrical stimulation may slightly reduce the duration of invasive mechanical ventilation; we are uncertain whether these results are found in subjects with COPD compared to subjects receiving usual care or placebo, and the quality of the body of evidence is low to very low. More RCTs are needed with a larger number of subjects, with more homogeneous diseases and basal conditions, and especially with a more adequate methodological design.

The solar drying of pig slurries was tested in a pilot-scale greenhouse (10 m2 footprint), operated with forced ventilation under low and high solar irradiation in Mediterranean conditions. Gaseous emissions were prevented through slurry acidification and by the biofiltration of exhaust gases. Air relative humidity and temperature in and out the greenhouse, as well as the weight of a slurry sample, were monitored online to command the ventilation regime. Daily average drying rate values ranged from 0.3 to 2.8 kg m&minus, 2 d&minus, 1 and displayed a direct dependency with solar radiation until the pig slurry lost a 60% of its initial weight, with a solar energy efficiency of about 26%. Upon further drying, the water content from pig slurries stabilized at around 10%. Mass balances between the initial slurry and dried product were closed for total solids and organic matter, but the recovery of nutrients ranged from 69% to 81%, apparently because of precipitation and incrustation phenomena. The NPK composition of the final product was 4.3&ndash, 2.5&ndash, 3.8 and fulfilled current regulations for solid organic fertilizers. Operational costs of the drying process and fertilizing quality parameters were also discussed.

Intensive livestock production has a negative environmental impact by producing large amounts of animal dejections, which, if not properly managed, can contaminate nearby water bodies with nutrient excess. However, if the animal manure could be transferred efficiently to nearby crops and used as a fertilizer for the plants, pollution/contamination would be mitigated, transforming manure from a waste to a resource. This valorization of manure from waste to a resource falls within the circular economy principles, but the transportation of manure also comes at an environmental and economic cost. It is a single-objective optimization problem regarding finding the best solution for the logistics process of satisfying nutrient crops needs through livestock manure. This paper uses a centralized optimal algorithm (COA) to solve the problem, based on a realistic simulator that considers numerous real-world constraints that related work has not yet addressed. Implementation and evaluation of this method have been carried out based on extensive geolocalized data from Catalonia (Spain), one of the densest European farming regions, as a case study. The findings show that the use of treatment units in pig farms is not profitable, while applying treatment units on selected cow farms for composting manure has its merits, under an intelligent choice of cow farms. Finally, a comparison of our findings with those of two similar studies in Hangzhou, China and Minnesota, USA, are performed. info:eu-repo/semantics/publishedVersion

Blockchain is an emerging digital technology allowing ubiquitous financial transactions among distributed untrusted parties, without the need of intermediaries such as banks. This chapter examines the impact of blockchain technology in agriculture and food supply chain, presents existing ongoing projects and initiatives, and discusses overall implications, challenges and potential, with a critical view over the maturity of these projects. Our findings indicate that blockchain is a promising technology towards a transparent supply chain of food, with many ongoing initiatives in various food products and food-related issues, but many barriers and challenges still exist, which hinder its wider popularity among farmers and systems. These challenges involve technical aspects, education, policies and regulatory frameworks., This work has been partly supported by the project that has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 739578 (RISE – Call: H2020-WIDESPREAD-01-2016-2017-TeamingPhase2) and the Republic of Cyprus through the Deputy Ministry of Research, Innovation and Digital Policy.

Soil organic carbon (SOC) plays an important role on improving soil conditions and soil functions. Increasing land use changes have induced an important decline of SOC content at global scale. Increasing SOC in agricultural soils has been proposed as a strategy to mitigate climate change. Animal manure has the characteristic of enriching SOC, when applied to crop fields, while, in parallel, it could constitute a natural fertilizer for the crops. In this paper, a simulation is performed using the area of Catalonia, Spain as a case study for the characteristic low SOC in the Mediterranean, to examine whether animal manure can improve substantially the SOC of agricultural fields, when applied as organic fertilizers. Our results show that the policy goals of the 4 × 1000 strategy can be achieved only partially by using manure transported to the fields. This implies that the proposed approach needs to be combined with other strategies.

Intensive livestock production might have a negative environmental impact, by producing large amounts of animal manure, which, if not properly managed, can contaminate nearby water bodies with nutrient excess. However, if animal manure is exported to nearby crop fields, to be used as organic fertilizer, pollution can be mitigated. It is a single-objective optimization problem, in regards to finding the best solution for the logistics process of satisfying nutrient needs of crops by means of livestock manure. This paper proposes three different approaches to solve the problem: a centralized optimal algorithm (COA), a decentralized nature-inspired cooperative technique, based on the foraging behaviour of ants (AIA), as well as a naive neighbour-based method (NBS), which constitutes the existing practice used today in an ad hoc, uncoordinated manner in Catalonia. Results show that the COA approach is 8.5% more efficient than the AIA. However, the AIA approach is fairer to the farmers and more balanced in terms of average transportation distances that need to be covered by each livestock farmer, while it is 1.07 times more eefficient than the NBS. Our work constitutes the first application of a decentralized AIA to this interesting real-world problem, in a domain where swarm intelligence methods are still under-exploited., Comment: Computers and Electronics in Agriculture Journal. arXiv admin note: substantial text overlap with arXiv:2006.04573

Streptococcus uberis is a worldwide pathogen that causes intramammary infections in dairy cattle. Nevertheless, commercial vaccines are currently not available and measures to control S. uberis mastitis are limited to the implementation of good management practices. The aim of the present study was to evaluate the efficacy of an S. uberis subunit vaccine against bovine mastitis (Laboratorios Hipra S.A., Amer, Spain) administered precalving against an experimental intramammary challenge with a heterologous S. uberis strain in dairy cows postcalving. With this objective, 25 gestating Holstein-Friesian heifers were randomly assigned to 1 of 2 groups: group 1 (n = 13), vaccinated by intramuscular route with the vaccine, and group 2 (n = 12), vaccinated by intramuscular route with phosphate-buffered saline as a control group. Both groups were immunized 60 and 21 d before the expected parturition date (75 and 36 d before challenge). Fourteen days after calving all cows were challenged by intramammary infusion of 100 colony-forming units of a heterologous S. uberis strain in 2 quarters per cow. Then, challenged quarters were monitored for clinical signs of mastitis, bacterial count, and somatic cell count for the following 21 d. Rectal temperature and daily milk yield per cow were also assessed. Results showed that all challenged quarters developed clinical mastitis. Nevertheless, vaccination significantly reduced the clinical signs of mastitis, bacterial count, rectal temperature, and daily milk yield losses after the intramammary infection and significantly increased the number of quarters with no bacterial isolation and somatic cell count

Survey on the practice of big data analysis in agriculture.Detailed review of 34 high-impact relevant research studies.Discussion on the status and potential of big data analysis in agriculture.Open problems and challenges, barriers for wider adoption and use.Ways to overcome barriers and potential future applications in agriculture. To tackle the increasing challenges of agricultural production, the complex agricultural ecosystems need to be better understood. This can happen by means of modern digital technologies that monitor continuously the physical environment, producing large quantities of data in an unprecedented pace. The analysis of this (big) data would enable farmers and companies to extract value from it, improving their productivity. Although big data analysis is leading to advances in various industries, it has not yet been widely applied in agriculture. The objective of this paper is to perform a review on current studies and research works in agriculture which employ the recent practice of big data analysis, in order to solve various relevant problems. Thirty-four different studies are presented, examining the problem they address, the proposed solution, tools, algorithms and data used, nature and dimensions of big data employed, scale of use as well as overall impact. Concluding, our review highlights the large opportunities of big data analysis in agriculture towards smarter farming, showing that the availability of hardware and software, techniques and methods for big data analysis, as well as the increasing openness of big data sources, shall encourage more academic research, public sector initiatives and business ventures in the agricultural sector. This practice is still at an early development stage and many barriers need to be overcome.

Intensive livestock production might have a negative environmental impact, by producing large amounts of animal excrements, which, if not properly managed, can contaminate nearby water bodies with nutrient excess. However, if animal manure is exported to distant crop fields, to be used as organic fertilizer, pollution can be mitigated. It is a single-objective optimization problem, in regards to finding the best solution for the logistics process of satisfying nutrient crops needs by means of livestock manure. This paper proposes a dynamic approach to solve the problem, based on a decentralized nature-inspired cooperative technique, inspired by the foraging behavior of ants (AIA). Results provide important insights for policy-makers over the potential of using animal manure as fertilizer for crop fields, while AIA solves the problem effectively, in a fair way to the farmers and well balanced in terms of average transportation distances that need to be covered by each livestock farmer. Our work constitutes the first application of a decentralized AIA to this interesting real-world problem, in a domain where swarm intelligence methods are still under-exploited., Comment: Proc. of the XXIVth International Society for Photogrammetry and Remote Sensing (ISPRS) Congress, June 2020

Blockchain is an emerging digital technology allowing ubiquitous financial transactions among distributed untrusted parties, without the need of intermediaries such as banks. This article examines the impact of blockchain technology in agriculture and food supply chain, presents existing ongoing projects and initiatives, and discusses overall implications, challenges and potential, with a critical view over the maturity of these projects. Our findings indicate that blockchain is a promising technology towards a transparent supply chain of food, with many ongoing initiatives in various food products and food-related issues, but many barriers and challenges still exist, which hinder its wider popularity among farmers and systems. These challenges involve technical aspects, education, policies and regulatory frameworks., Commentary published in Trends in Food Science & Technology Journal

Deep learning constitutes a recent, modern technique for image processing and data analysis, with promising results and large potential. As deep learning has been successfully applied in various domains, it has recently entered also the domain of agriculture. In this paper, we perform a survey of 40 research efforts that employ deep learning techniques, applied to various agricultural and food production challenges. We examine the particular agricultural problems under study, the specific models and frameworks employed, the sources, nature and pre-processing of data used, and the overall performance achieved according to the metrics used at each work under study. Moreover, we study comparisons of deep learning with other existing popular techniques, in respect to differences in classification or regression performance. Our findings indicate that deep learning provides high accuracy, outperforming existing commonly used image processing techniques. info:eu-repo/semantics/acceptedVersion

In many countries, it is difficult for government agencies to know where animal farms are located. Using satellite imaging and deep learning provides a new, effective, accurate and low-cost approach for detecting these facilities.

Intensive farming has been linked to significant degradation of land, water and air. A common body of knowledge is needed, to allow an effective monitoring of cropping systems, fertilization and water demands, and impacts of climate change, with a focus on sustainability and protection of the physical environment. In this paper, we describe AgriBigCAT, an online software platform that uses geophysical information from various diverse sources, employing geospatial and big data analysis, together with web technologies, in order to estimate the impact of the agricultural sector on the environment, considering land, water, biodiversity and natural areas requiring protection, such as forests and wetlands. This platform can assist both the farmers’ decision-taking processes and the administration planning and policy making, with the ultimate objective of meeting the challenge of increasing food production at a lower environmental impact.

Deep learning (DL) constitutes a modern technique for image processing, with large potential. Having been successfully applied in various areas, it has recently also entered the domain of agriculture. In the current paper, a survey was conducted of research efforts that employ convolutional neural networks (CNN), which constitute a specific class of DL, applied to various agricultural and food production challenges. The paper examines agricultural problems under study, models employed, sources of data used and the overall precision achieved according to the performance metrics used by the authors. Convolutional neural networks are compared with other existing techniques, and the advantages and disadvantages of using CNN in agriculture are listed. Moreover, the future potential of this technique is discussed, together with the authors’ personal experiences after employing CNN to approximate a problem of identifying missing vegetation from a sugar cane plantation in Costa Rica. The overall findings indicate that CNN constitutes a promising technique with high performance in terms of precision and classification accuracy, outperforming existing commonly used image-processing techniques. However, the success of each CNN model is highly dependent on the quality of the data set used.

Background Continuous aspiration of subglottic secretions is effective in preventing ventilator-associated pneumonia, but it involves a risk of mucosal damage. The main objective of our study was to determine the incidence of airway complications related to continuous aspiration of subglottic secretions. Methods In consecutive adult patients with continuous aspiration of subglottic secretions, we prospectively recorded clinical airway complications during the period after extubation. A multidetector computed tomography of the neck was performed during the period of 5 days following extubation to classify subglottic and tracheal lesions as mucosal thickening, cartilage thickening or deep ulceration. Results In the 86 patients included in the study, 6 (6.9%) had transient dyspnea, 7 (8.1%) had upper airway obstruction and 18 (20.9%) had dysphonia at extubation. Univariate analysis identified more attempts required for intubation (2.3 ± 1.1 vs. 1.2 ± 0.5; p = 0.001), difficult intubation (71.4 vs. 10.1%, p = 0.001) and Cormack score III–IV (71.4 vs. 8.8%; p

Environmental awareness and knowledge may help people to take more informed decisions in their everyday lives, ensuring their health and safety. The Web of Things enables embedded sensors to become easily deployed in urban areas for environmental monitoring such as air quality, electromagnetism, radiation, etc. In this paper, we propose an eco-system for urban computing which combines the concept of the Web of Things, together with big data analysis and event processing, towards the vision of smarter cities that offer real-time information to their habitants about the urban environment. We touch upon near real-time web-based discovery of sensory services, citizen participation, semantic technologies and mobile computing, helping people to take more informed everyday decisions when interacting with their urban landscape. We then present a case study where we demonstrate the feasibility and usefulness of this eco-system to the everyday lives of citizens. © 2017 IEEE. Sponsors: IEEE Communications Society (ComSoc) IEEE Region 8 University of Cyprus Conference code: 129751

With the recent advancement of the Internet of Things (IoT), it is now possible to process a large number of sensor data streams using different large-scale IoT platforms. These IoT frameworks are used to collect, process and analyse data streams in real-time and facilitate provision of smart solutions designed to provide decision support. Existing IoT-based solutions are mainly domain-dependent, providing stream processing and analytics focusing on specific areas (smart cities, healthcare etc.). In the context of agri-food industry, a variety of external parameters belonging to different domains (e.g. weather conditions, regulations etc.) have a major influence over the food supply chain, while flexible and adaptive IoT frameworks, essential to truly realize the concept of smart farming, are currently inexistent. In this paper, we propose Agri-IoT, a semantic framework for IoT-based smart farming applications, which supports reasoning over various heterogeneous sensor data streams in real-time. Agri-IoT can integrate multiple cross-domain data streams, providing a complete semantic processing pipeline, offering a common framework for smart farming applications. Agri-IoT supports large-scale data analytics and event detection, ensuring seamless interoperability among sensors, services, processes, operations, farmers and other relevant actors, including online information sources and linked open datasets and streams available on the Web.

Resumen Introduccion El carcinoma colorrectal es la tercera neoplasia mas frecuente y la segunda causa de muerte por cancer en los paises desarrollados. Aproximadamente el 10% de los pacientes con este diagnostico desarrollan metastasis pulmonares, Si bien solo el 2-4% de ellos tienen metastasis pulmonares como unica localizacion de recidiva. Objetivo Estudio de los factores pronostico de las metastasis pulmonares de carcinoma colorrectal. Pacientes y metodos Estudio observacional retrospectivo de 30 pacientes afectos de metastasis pulmonares de carcinoma colorrectal intervenidos quirurgicamente en nuestro centro desde enero de 2003 hasta diciembre de 2007. Resultados Se intervinieron un total de 30 pacientes, 19 varones (63%) y 11 mujeres (37%) con una edad media de 63,37 anos (intervalo 35-82 anos). La supervivencia global media fue de 36,64 meses (intervalo 18,58-54,70 meses). Para el analisis estadistico se consideraron 13 parametros, tanto preoperatorios como intra- y postoperatorios. En el analisis univariante, el numero de metastasis superior a 3 (p = 0,051), la bilateralidad (p = 0,001) y la bilobularidad (p Conclusiones En nuestra serie de pacientes afectos de metastasis pulmonares de carcinoma colorrectal, el numero de metastasis superior a tres, la bilobularidad y la bilateralidad resultaron factores de mal pronostico. Dichos factores deben tenerse en cuenta en el seguimiento de estos pacientes, aunque se necesitan estudios prospectivos con mayor numero de casos para confirmar dichos hallazgos.

The aim of this report is to show the MRI and CT findings for an extra-axial intracranial low-grade fibromyxoid sarcoma. To our knowledge, only three similar cases have been reported to date. We present the case of an 18-year-old woman who presented with a five-month history of hypoacusia, tinnitus, occipital headache, and left facial paresis. CT showed a large, homogeneous, expansive lesion in the left pontocerebellar angle that was eroding the promontory and affecting the posterior jugular foramen. At MRI, the lesion was homogeneous and isointense with respect to the cerebral parenchyma on T1-weighted sequences and heterogeneous and hypointense on T2-weighted sequences; after the administration of contrast material, it showed intense, homogeneous enhancement. The definitive diagnosis was established by histopathologic and immunohistochemical study.

As regulatory actions against copyright infringement have become to a large degree ineffective in the global context of Internet, new solutions balancing the interests of copyright owners, users and intermediaries were required. Semantic technology applied to Copyright may be considered an alternative to DRM or TPM systems, as metadata can be associated with a work, its title, author or right holder and intellectual property rights involved, so combining query languages and applications, the use or diffusion of those contents over the Internet can be controlled (authorizing or denying them) in what we named “Semantic Copyright”.

Intensive livestock farming has been linked to excessive pollution and contamination of land, water and air. A common body of knowledge is required in order to understand and assess this impact of agriculture, and take proper countermeasures with a focus on the sustainability and the protection of the physical environment, affecting agricultural productivity as little as possible. In this paper, we examine the problem of the environmental impact of livestock agriculture, targeting animal manure, which is a serious problem in various territories of Europe and the USA. Aiming to address this problem, we have developed AgriBigCAT, an online software platform that uses geophysical information from various diverse sources, employing geospatial and big data analysis, together with web technologies, in order to estimate the impact of the livestock agricultural sector on the environment, examining possible pollution of land, water and air, considering various scenarios and potential applications to mitigate the problem. The AgriBigCAT platform can assist both the farmers' decision-making processes and the administration planning and policy making, with the ultimate objective of meeting the challenge of increasing food production at a lower environmental impact.

Sinusitis fungica esfenoidal en paciente diabetica, con clinica inespecifica y signos de erosion osea radiologica a nivel sellar superior y retroclival. Tratada quirurgicamente por abordaje endoscopico transnasal y voriconazol oral. La histologia mostro hifas, descartando invasion mucosa y el estudio molecular detecto ADN de Phialemonium curvatum, un inusual patogeno.

Introduction: Lung metastases are the second leading cause of lung resection, constituting 30-40% of all surgeries performed in the field of Thoracic Surgery. Resection of pulmonary metastases is an open issue that generates various controversies. Depending on the functional respiratory capacity of the pulmonary metastatic patient, may come to consider multiple surgeries in the same patient, as many as the patient is able to tolerate by his or her respiratory reserve. Goal: Study of the results from surgical resection of pulmonary metastases in general and in particular those of colorectal origin. Patients and methods: Descriptive and observational retrospective study of 85 patients with pulmonary metastases who underwent surgery at our centre from January 2003 to December 2007. Results: Surgery was performed in 85 patients, 56 males (66%) and 29 women (34%) with a mean age of 55.14 years (range 22-82 years). The PMCRC (Pulmonary Metastases from Colorectal Cancer) correspond to 30 patients, meaning a 35% of all resected metastases. Next in frequency were the lung metastases of osteosarcoma, 16 (19%). And really close, metastases of soft tissue sarcoma, 11 (13%). The average overall survival from PM (Pulmonary Metastases) of colorectal origin was 36.64 months (range 18.58 to 54.70 months). If we break down the overall survival at one and three years, we get a probability of survival of 96% compared to 62%. Conclusions: Although surgery cannot change the biological essence of the metastatic process, complete resection of pulmonary metastases in appropriated selected patients, can provide a significant increase in survival or even a complete and permanent remission of the tumor.

The aim of this study was to characterize the CNS species isolated from cows included in a field trial to check the efficacy of Startvac© vaccine in a commercial dairy herd with subclinical CNS mastitis problems.

This is a case of fungal sphenoid sinusitis in a diabetic patient with non-specific symptoms and bone erosion radiological findings in the superior and posterior sphenoid walls. Surgical treatment was performed by transnasal endoscopic approach and voriconazole orally thereafter. The histopathological study found fungus hyphal without mucosa invasion and the molecular study determined DNA to be Phialemonium curvatum , an unusual pathogen.

e14515 Background: There is still controversy whether full lung palpation is required for patients undergoing pulmonary metastasectomy. We aimed to compare pulmonary ipsilateral recurrence (IR) aft...

The new technological advances should be accessible to the citizen, achieving this purpose through the development of informatic tools that speed up services’ rendering by the Administrations, taking into consideration the security aspects in these communications. The European AEQUITAS Project aims to develop an Informatic Tool that shall, via TCP/IP networks, allow secure communications and transmissions of electronic documents between juridical operators, using electronic signature and certification. The herein paper, describes in detail this Project, that can be encapsulated within the so-called Networked Government

The settlement of organic matter during composting was measured at different levels during the active biodegradation phase in forced-aerated static reactors loaded with different mixtures of organic wastes. The temperature evolution and the concentration of oxygen and carbon dioxide were also recorded in the exhaust gases. Two two-parameter equations and their generalised three-parameter form were fitted to the experimental data and their capability to predict settlement as a function of time was discussed. The settlement field inside the reactors was successfully described with a linear profile. At any given time and vertical position, mass settlement was proportional to the initial height after reactor loading. Furthermore, a relationship linking settlement to biological activity was also proposed. Under all tested experimental conditions, settlement showed a clear correlation with the cumulative oxygen consumption that was modelled with a three parameter equation.