Design, processing and testing of LSI arrays, hybrid microelectronics task

Mathematical cost models previously developed for hybrid microelectronic subsystems were refined and expanded. Rework terms related to substrate fabrication, nonrecurring developmental and manufacturing operations, and prototype production are included. Sample computer programs were written to demonstrate hybrid microelectric applications of these cost models. Computer programs were generated to calculate and analyze values for the total microelectronics costs. Large scale integrated (LST) chips utilizing tape chip carrier technology were studied. The feasibility of interconnecting arrays of LSU chips utilizing tape chip carrier and semiautomatic wire bonding technology was demonstrated

Fatty acid profiles of varietal virgin olive oils (<i>Olea europaea</i> L.) from mature orchards in warm arid valleys of Northwestern Argentina (La Rioja)

The olive industry in Northwestern Argentina has experienced substantial growth during the past two decades to produce virgin olive oil for export. To assess the fatty acid profiles of the main varietal olive oils, 563 oil samples from 17 varieties cultivated in the province of La Rioja were analyzed from 2005-2008. Olive varieties were ranked according to oleic acid content as low (<55%; Arbequina, Arauco), intermediate (55-65%; Barnea, Frantoio) or high (>65%; Manzanilla, Empeltre, Leccino, Coratina, Changlot, Picual). Using data from this study and the literature, the fatty acid composition of Spanish (Arbequina, Picual) and Italian (Coratina, Frantoio) varieties indicated consistently lower oleic acid contents when grown in NW Argentina versus the Mediterranean. For Arbequina, the oleic content decreased with increasing temperature during oil accumulation (-2% per °C). The classification of varieties should be useful in the selection of virgin olive oils for corrective blending and for choosing varieties for new orchards in order to meet IOOC requirements. The differences in fatty acid composition between NW Argentina and the Mediterranean Basin are most likely to be related to a genotype produced by environmental interaction, and the negative effect of the high seasonal mean temperature during oil accumulation will need further research.<br><br>La industria oleícola del noroeste de Argentina creció sustancialmente durante las últimas dos décadas para producir aceite de oliva virgen exportable. Para evaluar el perfil de ácidos grasos de los principales aceites varietales, se analizaron 563 muestras de aceite de 17 variedades en la provincia de La Rioja durante 2005-2008. Las variedades se clasificaron de acuerdo a su contenido de ácido oleico en bajo (<55%; Arbequina, Arauco), medio (55-65%; Barnea, Frantoio), o alto (>65%; Manzanilla, Empeltre, Leccino, Coratina, Changlot, Picual). Utilizando datos de este trabajo y de la literatura, los aceites de variedades de origen español (Arbequina y Picual) e italiano (Coratina y Frantoio) mostraron consistentemente menor contenido de ácido oleico cuando crecieron en el noroeste de Argentina versus el Mediterráneo. Para Arbequina, el contenido de oleico disminuyó con la temperatura durante la síntesis y acumulación lipídica (-2 % por °C). La clasificación varietal por acido oleico debe ser útil para seleccionar aceites para mezclas correctivas y variedades para futuras plantaciones que cumplan con la normativa del COI. Diferencias en los perfiles de ácidos grasos entre el noroeste de Argentina y el Mediterráneo indican una interacción genotipo x ambiente, y el efecto negativo de la alta temperatura media estacional durante la síntesis de lípidos requerirá mayor investigación

Estudios de la transformación enzimática de derivados de adamantano con cepas de hongos de los géneros aspergillus y fusarium, y sus potenciales actividades biológica

La idea es presentar el proyecto a la comunidad universitaria, teniendo en cuenta que el mismo se desarrolla entre la Facultadde Ciencias de la Alimentación, Bioquímicas y Farmacéuticas y el área Química del Instituto de Ciencias Básicas de la Universidad Nacionalde San Juan.  Está dirigido a la obtención de compuestos novedosos a partir de sustratos orgánicos derivados de adamantano, a través de su funcionalización utilizando catalizadores biológicos (enzimas), producidos por microorganismos (hongos filamentosos). Los metabolitos obtenidos serán aislados, purificados y analizados por métodos espectroscópicos para determinar su estructura. Los compuestos puros obtenidos por esta técnica, serán evaluados in vitro en su actividad sobre la acción tóxica de NMDA midiendo viabilidad y muerte celular

La hoja de olea europaea L….¿Un recurso aprovechable en la industria farmacéutica?

Es de conocimiento que la provincia de San Juan reúne las condiciones necesarias para el cultivo económico de la planta de olivo, contando además con importantes organizaciones, instaladas en nuestra Facultad, dedicadas a la olivicultura. Es por ello y debido a la gran importancia que ha tomado en nuestra provincia el cultivo de dicha planta y sabiendo que la mayor parte de los estudios desde el aspecto científico se han enfocado hacia los beneficios del aceite y sus características, se ve necesario el inicio de investigaciones que nos conduzcan a estudiar la existencia de compuestos de interés en las partes menos analizadas del cultivo, como la foliar, con fines medicinales, farmacéuticos y agropecuarios

Downregulation of miR-99a/let-7c/miR-125b miRNA cluster predicts clinical outcome in patients with unresected malignant pleural mesothelioma

Malignant pleural mesothelioma (MPM) is an aggressive tumor with a dismal overall survival (OS) and to date no molecular markers are available to guide patient management. This study aimed to identify a prognostic miRNA signature in MPM patients who did not undergo tumor resection. Whole miRNA profiling using a microarray platform was performed using biopsies on 27 unresected MPM patients with distinct clinical outcome: 15 patients had short survival (OS &lt; 12 months) and 12 patients had long survival (OS &gt; 36 months). Three prognostic miRNAs (mir- 99a, let-7c, and miR-125b) encoded at the same cluster (21q21) were selected for further validation and tested on publicly available miRNA sequencing data from 72 MPM patients with survival data. A risk model was built based on these 3 miRNAs that was validated by quantitative PCR in an independent set of 30 MPM patients. High-risk patients had shorter median OS (7.6 months) as compared with low-risk patients (median not reached). In the multivariate Cox model, a high-risk score was independently associated with shorter OS (HR=3.14; 95% CI, 1.18-8.34; P=0.022). Our study identified that the downregulation of the miR-99a/let-7/miR-125b miRNA cluster predicts poor outcome in unresected MPM

Identification of a 5-Protein Biomarker Molecular Signature for Predicting Alzheimer's Disease

Background: Alzheimer’s disease (AD) is a progressive brain disease with a huge cost to human lives. The impact of the disease is also a growing concern for the governments of developing countries, in particular due to the increasingly high number of elderly citizens at risk. Alzheimer’s is the most common form of dementia, a common term for memory loss and other cognitive impairments. There is no current cure for AD, but there are drug and non-drug based approaches for its treatment. In general the drug-treatments are directed at slowing the progression of symptoms. They have proved to be effective in a large group of patients but success is directly correlated with identifying the disease carriers at its early stages. This justifies the need for timely and accurate forms of diagnosis via molecular means. We report here a 5-protein biomarker molecular signature that achieves, on average, a 96% total accuracy in predicting clinical AD. The signature is composed of the abundances of IL-1α, IL-3, EGF, TNF-α and G-CSF. Methodology/Principal Findings: Our results are based on a recent molecular dataset that has attracted worldwide attention. Our paper illustrates that improved results can be obtained with the abundance of only five proteins. Our methodology consisted of the application of an integrative data analysis method. This four step process included: a) abundance quantization, b) feature selection, c) literature analysis, d) selection of a classifier algorithm which is independent of the feature selection process. These steps were performed without using any sample of the test datasets. For the first two steps, we used the application of Fayyad and Irani’s discretization algorithm for selection and quantization, which in turn creates an instance of the (alpha-beta)-k-Feature Set problem; a numerical solution of this problem led to the selection of only 10 proteins. Conclusions/Significance: the previous study has provided an extremely useful dataset for the identification of A biomarkers. However, our subsequent analysis also revealed several important facts worth reporting: 1. A 5-protein signature (which is a subset of the 18-protein signature of Ray et al.) has the same overall performance (when using the same classifier). 2. Using more than 20 different classifiers available in the widely-used Weka software package, our 5- protein signature has, on average, a smaller prediction error indicating the independence of the classifier and the robustness of this set of biomarkers (i.e. 96% accuracy when predicting AD against non-demented control). 3. Using very simple classifiers, like Simple Logistic or Logistic Model Trees, we have achieved the following results on 92 samples: 100 percent success to predict Alzheimer’s Disease and 92 percent to predict Non Demented Control on the AD dataset

A combinatorial framework to quantify peak/pit asymmetries in complex dynamics

LL’s acknowledges funding from an EPSRC Early Career Fellowship EP/P01660X/1

Evaluation of a Previously Suggested Plasma Biomarker Panel to Identify Alzheimer's Disease

There is an urgent need for biomarkers in plasma to identify Alzheimer's disease (AD). It has previously been shown that a signature of 18 plasma proteins can identify AD during pre-dementia and dementia stages (Ray et al, Nature Medicine, 2007). We quantified the same 18 proteins in plasma from 174 controls, 142 patients with AD, and 88 patients with other dementias. Only three of these proteins (EGF, PDG-BB and MIP-1δ) differed significantly in plasma between controls and AD. The 18 proteins could classify patients with AD from controls with low diagnostic precision (area under the ROC curve was 63%). Moreover, they could not distinguish AD from other dementias. In conclusion, independent validation of results is important in explorative biomarker studies

Metabolomics-Based Discovery of Diagnostic Biomarkers for Onchocerciasis

Onchocerciasis, caused by the filarial parasite Onchocerca volvulus, afflicts millions of people, causing such debilitating symptoms as blindness and acute dermatitis. There are no accurate, sensitive means of diagnosing O. volvulus infection. Clinical diagnostics are desperately needed in order to achieve the goals of controlling and eliminating onchocerciasis and neglected tropical diseases in general. In this study, a metabolomics approach is introduced for the discovery of small molecule biomarkers that can be used to diagnose O. volvulus infection. Blood samples from O. volvulus infected and uninfected individuals from different geographic regions were compared using liquid chromatography separation and mass spectrometry identification. Thousands of chromatographic mass features were statistically compared to discover 14 mass features that were significantly different between infected and uninfected individuals. Multivariate statistical analysis and machine learning algorithms demonstrated how these biomarkers could be used to differentiate between infected and uninfected individuals and indicate that the diagnostic may even be sensitive enough to assess the viability of worms. This study suggests a future potential of these biomarkers for use in a field-based onchocerciasis diagnostic and how such an approach could be expanded for the development of diagnostics for other neglected tropical diseases