Experimental Analysis of Fiber Reinforcement Rings' Effect on Tensile and Flexural Properties of Onyx™-Kevlar® Composites Manufactured by Continuous Fiber Reinforcement.

Additive manufacturing of composite materials is progressing in the world of 3D printing technologies; composite materials allow the combination of the physical and mechanical properties of two or more constituents to create a new material that meets the required properties of several applications. In this research, the impact of adding Kevlar® reinforcement rings on the tensile and flexural properties of the Onyx™ (nylon with carbon fibers) matrix was analyzed. Parameters such as infill type, infill density and fiber volume percentage were controlled to determine the mechanical response in tensile and flexural tests of the additive manufactured composites. The tested composites showed an increment of four times the tensile modulus and 1.4 times the flexural modulus of pure Onyx™ matrix when compared with that of the Onyx™-Kevlar®. The experimental measurements demonstrated that Kevlar® reinforcement rings can increase the tensile and flexural modulus of Onyx™-Kevlar® composites using low fiber volume percentages (lower than 19% in both samples) and 50% of rectangular infill density. However, the appearance of some defects, such as delamination, was observed and should be further analyzed to obtain products that are errorless and can be reliable for real functions as in automotive or aeronautical industries.

Complejo esclerosis tuberosa: diagnóstico, manejo pre y posnatal: reporte de un caso clínico / Tuberous sclerosis complex: diagnosis, pre and postnatal management: report of a clinical case

El Complejo Esclerosis Tuberosa es un síndrome neurocutáneo multisistémico producido por un padecimiento genético hereditario de carácter autosómico dominante de alta penetrancia y una expresividad variable. Afecta a muchos órganos, principalmente a la piel, cerebro, sistema nervioso, riñones y corazón. La causa es una mutación en uno de los genes TSC1 o TSC2; se ha estimado que su incidencia es de 1 en 5.000 a 10.000 nacidos vivos. Se reporta el caso clínico de una gestante derivado al servicio de Ginecología y Obstetricia del Hospital Obrero No 2 de la Caja Nacional de Salud por hallazgo ecográfico cardiaco anormal. El estudio morfológico en el servicio concluyó que se trataba de una probable esclerosis tuberosa; al término del embarazo se realizó cesárea abdominal por causa obstétrica. Los estudios postnatales confirmaron los hallazgos.

The Tuberous Sclerosis Complex is a multisystem neurocutaneous syndrome produced by a hereditary genetic disease of an autosomal dominant gene with high penetrance and variable expressiveness. It affects many organs mainly to the skin, brain, nervous system, kidneys and heart. The cause is a mutation in one of the genes TSC1 or TSC2; it has been considered that its incidence is 1 in 5.000 to 10.000 born alive. The clinical case of a pregnant woman was reported and referred to the Gynecology and Obstetrics service of the Obrero Hospital No 2 of the Caja Nacional de Salud due to an abnormal cardiac ultrasound finding. The morphological study in the service concluded that it was about a probable tuberous sclerosis; at the end of the pregnancy, a cesarean surgery was performed for obstetrical reasons. The postnatal studies confirmed the discoveries.

Cardiovascular risk in women attending primary care centres: baseline data of the EVA study.

BACKGROUND: The purpose of this study was to determine the prevalence of hypertension, cardiovascular risk factors and target organ damage using baseline data from the EVA study. METHODS: EVA is a 5-year multicentre prospective study of women aged between 40 and 70 years attending primary care centres in a rural-urban area in the north of Spain. The recruitment period was between October 2009 and January 2010. The following variables were analysed: associated cardiovascular risk factors, target organ damage and cardiovascular or renal disease defined according to the 2007 European Society of Hypertension and the European Society of Cardiology Guidelines (2007 ESH/ESC 2007). Blood pressure <140/90 mmHg and <130/80 in diabetics were considered target blood pressure values. Cardiovascular risk was stratified according to the 2007 ESC-ESH guidelines. RESULTS: The study sample comprised of 903 women with a mean age of 59.6 ± 8 years. The prevalence of hypertension, Type 2 diabetes and dyslipidaemia was 45.6, 13.3 and 41.7%, respectively. Target organ damage affected 17.6% of women and manifested as microalbuminuria (1.8%), slight increase in plasma creatinine (1.6%) and left ventricular hypertrophy (2.9%). Overall, 9.3% had cardiovascular disease, 3.4% coronary heart disease, 1.8% heart failure, 1.8% peripheral artery disease and 1.4% renal disease; 2.2% of patients had experienced a stroke. The prevalence of cardiovascular risk factors in hypertensive women (HT) with respect to non-hypertensive women (NHT) was as follows: obesity 44.7 versus 18.9%, dyslipidaemia 48.8 versus 35.8% and Type 2 diabetes 21.8 versus 6.1%. The target organ damage was more prevalent in hypertensive women: 27.3 versus 9.4%. Cardiovascular disease was present in 14.8% of HT and 4.7% of NHT. High or very high cardiovascular risk affected 65.3% of HT and 26.9% of NHT. CONCLUSIONS: Four in 10 women attending primary care centres had a high or very high cardiovascular risk. Percentages of classic cardiovascular risk factors were higher in HT than in NHT and increased significantly with age. The most commonly used drugs were renin-angiotensin system blockers and diuretics.

The effect of combining two echo times in automatic brain tumor classification by MRS.

(1)H MRS is becoming an accurate, non-invasive technique for initial examination of brain masses. We investigated if the combination of single-voxel (1)H MRS at 1.5 T at two different (TEs), short TE (PRESS or STEAM, 20-32 ms) and long TE (PRESS, 135-136 ms), improves the classification of brain tumors over using only one echo TE. A clinically validated dataset of 50 low-grade meningiomas, 105 aggressive tumors (glioblastoma and metastasis), and 30 low-grade glial tumors (astrocytomas grade II, oligodendrogliomas and oligoastrocytomas) was used to fit predictive models based on the combination of features from short-TEs and long-TE spectra. A new approach that combines the two consecutively was used to produce a single data vector from which relevant features of the two TE spectra could be extracted by means of three algorithms: stepwise, reliefF, and principal components analysis. Least squares support vector machines and linear discriminant analysis were applied to fit the pairwise and multiclass classifiers, respectively. Significant differences in performance were found when short-TE, long-TE or both spectra combined were used as input. In our dataset, to discriminate meningiomas, the combination of the two TE acquisitions produced optimal performance. To discriminate aggressive tumors from low-grade glial tumours, the use of short-TE acquisition alone was preferable. The classifier development strategy used here lends itself to automated learning and test performance processes, which may be of use for future web-based multicentric classifier development studies.

Situación de la tuberculosis en el Perú: Informe de gestión / TB situation in Peru: Management Report

El presente documento considera como una prioridad sanitaria nacional, la tuberculosis en el Perú, debido a que la tuberculosis es una enfermedad endémica y afecta a nuestra población pobre y extremadamente pobre que es la de mayor vulnerabilidad, mermando su calidad de vida, contribuyendo a perpetuar el ciclo de pobreza ecxistente(AU)

Situación de la tuberculosis en el Perú: Informe de gestión / TB situation in Peru: Management Report

El presente documento considera como una prioridad sanitaria nacional, la tuberculosis en el Perú, debido a que la tuberculosis es una enfermedad endémica y afecta a nuestra población pobre y extremadamente pobre que es la de mayor vulnerabilidad, mermando su calidad de vida, contribuyendo a perpetuar el ciclo de pobreza ecxistente

Benign/malignant classifier of soft tissue tumors using MR imaging.

UNLABELLED: This article presents a pattern-recognition approach to the soft tissue tumors (STT) benign/malignant character diagnosis using magnetic resonance (MR) imaging applied to a large multicenter database. OBJECTIVE: To develop and test an automatic classifier of STT into benign or malignant by using classical MR imaging findings and epidemiological information. MATERIALS AND METHODS: A database of 430 patients (62% benign and 38% malignant) from several European multicenter registers. There were 61 different histologies (36 with benign and 25 with malignant nature). Three pattern-recognition methods (artificial neural networks, support vector machine, k-nearest neighbor) were applied to learn the discrimination between benignity and malignancy based on a defined MR imaging findings protocol. After the systems had learned by using training samples (with 302 cases), the clinical decision support system was tested in the diagnosis of 128 new STT cases. RESULTS: An 88-92% efficacy was obtained in a not-viewed set of tumors using the pattern-recognition techniques. The best results were obtained with a back-propagation artificial neural network. CONCLUSION: Benign vs. malignant STT discrimination is accurate by using pattern-recognition methods based on classical MR image findings. This objective tool will assist radiologists in STT grading.

Medical decision support system for diagnosis of soft tissue tumors based on distributed architecture.

This paper introduces a novel distributed decision support system to help radiologists in the diagnosis of soft tissue tumors (STT). Decision support systems are based on pattern recognition engines that discriminate between benign/malignant character and histological groups with a satisfactory estimated efficiency. This system is based on a distributed architecture with three specialized nodes: Radiologist Visual Interface, Information System and Decision Support Web-services. The visual interface is the radiologists and clinicians' point of access to local and remote STT registers, statistical analysis tools and distributed pattern recognition engines. A location-independent and multi-platform system has been developed in order to connect hospitals and institutions to research useful tools in clinical and laboratory environments. The nodes maintenance and upgrade are automatically controlled by the architecture. This tool will be useful regarding the objective methodology to assist radiologist decision in a new case and will help the education of the new radiologists with no expertise in STT.