Unicoloniality, recognition and genetic differentiation in a native Formica ant.

Some ants have an extraordinary form of social organization, called unicoloniality, whereby individuals mix freely among physically separated nests. This mode of social organization has been primarily studied in introduced and invasive ant species, so that the recognition ability and genetic structure of ants forming unicolonial populations in their native range remain poorly known. We investigated the pattern of aggression and the genetic structure of six unicolonial populations of the ant Formica paralugubris at four hierarchical levels: within nests, among nests within the same population, among nests of populations within the Alps or Jura Mountains and among nests of the two mountain ranges. Ants within populations showed no aggressive behaviour, but recognized nonnestmates as shown by longer antennation bouts. Overall, the level of aggression increased with geographic and genetic distance but was always considerably lower than between species. No distinct behavioural supercolony boundaries were found. Our study provides evidence that unicoloniality can be maintained in noninvasive ants despite significant genetic differentiation and the ability to discriminate between nestmates and nonnestmates.

Accreditation of forensic pathology service: a priviledge or a nightmare?

Forensic experts play a major role in the legal process as they offer professional expert opinion and evidence within the criminal justice system adjudicating on the innocence or alleged guilt of an accused person. In this respect medico-legal examination is an essential part of the investigation process, determining in a scientific way, the cause(s) and manner of unexpected and/or unnatural death or bringing clinical evidence in case of physical, psychological or sexual abuse in living people. From a legal perspective, these types of investigation must meet international standards i-e it should be independent, effective and prompt. Ideally the investigations should be conducted by board certified experts in forensic medicine, endowed with a solid experience in this field, without any hierarchical relationship with the prosecuting authorities and having access to appropriate facilities in order to provide forensic reports of high quality. In this respect, there is a need for any private or public national or international authority including non-governmental organisations seeking experts qualified in forensic medicine,to have at disposal a list of specialists working in accordance with high standards of professional performance within forensic pathology services that have been successfully submitted to an official accreditation/certification process using valid and acceptable criteria. To reach this goal the National Association of Medical examiners (NAME) has elaborated an accreditation/certification check-list which should be served as decision-making support to assist inspectors appointed to evaluate applicants. In the same spirit than NAME Accreditation Standards, ECLM board decided to set up an ad hoc working group with the mission to elaborate an accreditation/certification procedure similar to the NAME's one but taking into account the realities of forensic medicine practices in Europe and restricted to post-mortem investigations. This accreditation process applies to services and not to individual practitioners by emphasizing policies and procedures rather than professional performance. In addition the standards to be complied with should be considered as the minimum standards needed to get the recognition of performing and reliable forensic pathology service.

Land use/cover classification in the Brazilian Amazon using satellite images

Land use/cover classification is one of the most important applications in remote sensing. However, mapping accurate land use/cover spatial distribution is a challenge, particularly in moist tropical regions, due to the complex biophysical environment and limitations of remote sensing data per se. This paper reviews experiments related to land use/cover classification in the Brazilian Amazon for a decade. Through comprehensive analysis of the classification results, it is concluded that spatial information inherent in remote sensing data plays an essential role in improving land use/cover classification. Incorporation of suitable textural images into multispectral bands and use of segmentation‑based method are valuable ways to improve land use/cover classification, especially for high spatial resolution images. Data fusion of multi‑resolution images within optical sensor data is vital for visual interpretation, but may not improve classification performance. In contrast, integration of optical and radar data did improve classification performance when the proper data fusion method was used. Among the classification algorithms available, the maximum likelihood classifier is still an important method for providing reasonably good accuracy, but nonparametric algorithms, such as classification tree analysis, have the potential to provide better results. However, they often require more time to achieve parametric optimization. Proper use of hierarchical‑based methods is fundamental for developing accurate land use/cover classification, mainly from historical remotely sensed data.

A cophenetic correlation coefficient for Tocher's method

The objective of this work was to propose a way of using the Tocher's method of clustering to obtain a matrix similar to the cophenetic one obtained for hierarchical methods, which would allow the calculation of a cophenetic correlation. To illustrate the obtention of the proposed cophenetic matrix, we used two dissimilarity matrices - one obtained with the generalized squared Mahalanobis distance and the other with the Euclidean distance - between 17 garlic cultivars, based on six morphological characters. Basically, the proposal for obtaining the cophenetic matrix was to use the average distances within and between clusters, after performing the clustering. A function in R language was proposed to compute the cophenetic matrix for Tocher's method. The empirical distribution of this correlation coefficient was briefly studied. For both dissimilarity measures, the values of cophenetic correlation obtained for the Tocher's method were higher than those obtained with the hierarchical methods (Ward's algorithm and average linkage - UPGMA). Comparisons between the clustering made with the agglomerative hierarchical methods and with the Tocher's method can be performed using a criterion in common: the correlation between matrices of original and cophenetic distances.

Gestión de confianza en redes ad hoc

El despliegue de un esquema de confianza es fundamental para poder desarrollar servicios de seguridad que permitan administrar y operar una red. Sin embargo, las soluciones empleadas en las redes tradicionales no se adaptan a un entorno ad hoc debido a la naturaleza dinámica y sin infraestructura de estas redes. En el presente trabajo se propone un esquema de confianza práctico y eficiente basado en una infraestructura de clave pública distribuida, umbral y jerárquica, que no requiere sincronización temporal entre todos los nodos de la red. La autorización de usuarios en el sistema se hace a través de certificados de corta duración que eliminan la necesidad de mantener la publicación y diseminación de unas listas de revocación. Por otro lado, una entidad externa de confianza permite alargar la reputación de un usuario de la red más allá de la existencia de la propia red.

Comparison of molecular signatures from multiple skin diseases identifies mechanisms of immunopathogenesis.

The ability to obtain gene expression profiles from human disease specimens provides an opportunity to identify relevant gene pathways, but is limited by the absence of data sets spanning a broad range of conditions. Here, we analyzed publicly available microarray data from 16 diverse skin conditions in order to gain insight into disease pathogenesis. Unsupervised hierarchical clustering separated samples by disease as well as common cellular and molecular pathways. Disease-specific signatures were leveraged to build a multi-disease classifier, which predicted the diagnosis of publicly and prospectively collected expression profiles with 93% accuracy. In one sample, the molecular classifier differed from the initial clinical diagnosis and correctly predicted the eventual diagnosis as the clinical presentation evolved. Finally, integration of IFN-regulated gene programs with the skin database revealed a significant inverse correlation between IFN-β and IFN-γ programs across all conditions. Our study provides an integrative approach to the study of gene signatures from multiple skin conditions, elucidating mechanisms of disease pathogenesis. In addition, these studies provide a framework for developing tools for personalized medicine toward the precise prediction, prevention, and treatment of disease on an individual level.

Classification and fingerprinting of different berries based on biochemical profiling and antioxidant capacity

The objective of this work was to evaluate the biochemical composition of six berry types belonging to Fragaria, Rubus, Vaccinium and Ribes genus. Fruit samples were collected in triplicate (50 fruit each) from 18 different species or cultivars of the mentioned genera, during three years (2008 to 2010). Content of individual sugars, organic acids, flavonols, and phenolic acids were determined by high performance liquid chromatography (HPLC) analysis, while total phenolics (TPC) and total antioxidant capacity (TAC), by using spectrophotometry. Principal component analysis (PCA) and hierarchical cluster analysis (CA) were performed to evaluate the differences in fruit biochemical profile. The highest contents of bioactive components were found in Ribes nigrum and in Fragaria vesca, Rubus plicatus, and Vaccinium myrtillus. PCA and CA were able to partially discriminate between berries on the basis of their biochemical composition. Individual and total sugars, myricetin, ellagic acid, TPC and TAC showed the highest impact on biochemical composition of the berry fruits. CA separated blackberry, raspberry, and blueberry as isolate groups, while classification of strawberry, black and red currant in a specific group has not occurred. There is a large variability both between and within the different types of berries. Metabolite fingerprinting of the evaluated berries showed unique biochemical profiles and specific combination of bioactive compound contents.