The Loss of Functional Caspase-12 in Europe Is a Pre-Neolithic Event

6 p.

High-Throughput Sequencing of microRNAs in Peripheral Blood Mononuclear Cells: Identification of Potential Weight Loss Biomarkers

INTRODUCTION: MicroRNAs (miRNAs) are being increasingly studied in relation to energy metabolism and body composition homeostasis. Indeed, the quantitative analysis of miRNAs expression in different adiposity conditions may contribute to understand the intimate mechanisms participating in body weight control and to find new biomarkers with diagnostic or prognostic value in obesity management. OBJECTIVE: The aim of this study was the search for miRNAs in blood cells whose expression could be used as prognostic biomarkers of weight loss. METHODS: Ten Caucasian obese women were selected among the participants in a weight-loss trial that consisted in following an energy-restricted treatment. Weight loss was considered unsuccessful when <5% of initial body weight (non-responders) and successful when >5% (responders). At baseline, total miRNA isolated from peripheral blood mononuclear cells (PBMC) was sequenced with SOLiD v4. The miRNA sequencing data were validated by RT-PCR. RESULTS: Differential baseline expression of several miRNAs was found between responders and non-responders. Two miRNAs were up-regulated in the non-responder group (mir-935 and mir-4772) and three others were down-regulated (mir-223, mir-224 and mir-376b). Both mir-935 and mir-4772 showed relevant associations with the magnitude of weight loss, although the expression of other transcripts (mir-874, mir-199b, mir-766, mir-589 and mir-148b) also correlated with weight loss. CONCLUSIONS: This research addresses the use of high-throughput sequencing technologies in the search for miRNA expression biomarkers in obesity, by determining the miRNA transcriptome of PBMC. Basal expression of different miRNAs, particularly mir-935 and mir-4772, could be prognostic biomarkers and may forecast the response to a hypocaloric diet.

Influence of Training Set Selection in Artificial Neural Network-Based Propagation Path Loss Predictions

This paper analyzes the use of artificial neural networks (ANNs) for predicting the received power/path loss in both outdoor and indoor links. The approach followed has been a combined use of ANNs and ray-tracing, the latter allowing the identification and parameterization of the so-called dominant path. A complete description of the process for creating and training an ANN-based model is presented with special emphasis on the training process. More specifically, we will be discussing various techniques to arrive at valid predictions focusing on an optimum selection of the training set. A quantitative analysis based on results from two narrowband measurement campaigns, one outdoors and the other indoors, is also presented.

Accelerating loss of seagrasses across the globe threatens coastal ecosystems

Coastal ecosystems and the services they provide are adversely affected by a wide variety of human activities. In particular, seagrass meadows are negatively affected by impacts accruing from the billion or more people who live within 50 km of them. Seagrass meadows provide important ecosystem services, including an estimated $1.9 trillion per year in the form of nutrient cycling; an order of magnitude enhancement of coral reef fish productivity; a habitat for thousands of fish, bird, and invertebrate species; and a major food source for endangered dugong, manatee, and green turtle. Although individual impacts from coastal development, degraded water quality, and climate change have been documented, there has been no quantitative global assessment of seagrass loss until now. Our comprehensive global assessment of 215 studies found that seagrasses have been disappearing at a rate of 110 square kilometers per year since 1980 and that 29% of the known areal extent has disappeared since seagrass areas were initially recorded in 1879. Furthermore, rates of decline have accelerated from a median of 0.9% per year before 1940 to 7% per year since 1990. Seagrass loss rates are comparable to those reported for mangroves, coral reefs, and tropical rainforests and place seagrass meadows among the most threatened ecosystems on earth.

Kommentar zum Worm-et-al.-Artikel„Impacts of Biodiversity Loss on Ocean Ecosystem Services“: erschienen im Wissenschaftsmagazin Science, Vol. 314, am 3. November 2006

Folgende Kernbehauptungen bzw. Hypothesen werden in dem Worm-et-al.-Artikel aufgestellt: -Der Verlust an Biodiversität (Artenzahl) in einem Meeresgebiet reduziert tief greifend seine Produktivität und seine Stabilität in Stressperioden, hervorgerufen u.a. durch Überfischung und Klimaänderung. -Die Zahl der kollabierten Arten nimmt zu. Dieser Trend projeziert den Kollaps aller wildlebenden Arten und Bestände, die gegenwärtig befischt werden, auf das Jahr 2048. -Diese Entwicklung ist zum gegenwärtigen Zeitpunkt reversibel, denn das Meer besitzt noch ein großes Potential sich zu regenerieren. Dazu ist aber mehr Umweltschutz notwendig.