New insights on the external features of egg capsules and embryo development in the squid Loligo vulgaris

The embryonic development of the squid Loligo vulgaris was observed from 183 egg masses collected from special devices deployed throughout Cabrera National Park (Baleares Islands, western Mediterranean Sea). Sequence alignment analysis of the cytochrome oxidase I gene revealed that all embryos belonged to L. vulgaris. In total, 549 egg capsules were examined. Viable egg capsules (n = 420) were classified into one of five maturation stages according to the primary external features. The length of the viable egg capsules varied between 40 and 170 mm, and increased with embryonic development. The non-viable capsules (n = 129) were categorized into four groups: I (Ginger root), non-viable II and III, and empty egg capsule (IV). The percentage of non-viable capsules (i.e. grades I, II and III) was 92.25%. Empty capsules accounted for 7.75% of the total non-viable egg capsules. Embryonic development was classified into a second scale of eight stages. Egg capsule stage and embryonic stage were significantly related (n = 420; p < 0.001), facilitating the determination of the embryo developmental phase based on the outward appearance of the egg capsules. The embryo development stage based on the external features of the egg capsules might constitute an innovative tool for in situ embryological data collection. This new method is neither time consuming nor invasive, and could be helpful in fishing cruises, for scuba diving visual census in natural habitats and for laboratory culture. Slight variability in the developmental embryonic stages within egg capsules from the same egg mass was identified. The origin of this asynchrony is discussed. Chronological appearance of organs was similar to that of the six loliginid species previously examined. However, some developmental changes in the timing or rate of events (heterochronies) were observed: Hoyle’s organ was formed earlier in L. vulgaris and the appearance of ventral chromatophores was slightly delayed (2 days) compared with the other species considered.     

Dealing with Distances and Transformations for Fuzzy C-Means Clustering of Compositional Data

Clustering techniques are based upon a dissimilarity or distance measure between objects and clusters. This paper focuses on the simplex space, whose elements??compositions??are subject to non-negativity and constant-sum constraints. Any data analysis involving compositions should fulfill two main principles: scale invariance and subcompositional coherence. Among fuzzy clustering methods, the FCM algorithm is broadly applied in a variety of fields, but it is not well-behaved when dealing with compositions. Here, the adequacy of different dissimilarities in the simplex, together with the behavior of the common log-ratio transformations, is discussed in the basis of compositional principles. As a result, a well-founded strategy for FCM clustering of compositions is suggested. Theoretical findings are accompanied by numerical evidence, and a detailed account of our proposal is provided. Finally, a case study is illustrated using a nutritional data set known in the clustering literature.     

Playing Dissymmetry in Action Research: The Role of Power and Differences in Promoting Participative Knowledge and Change

This article explores the importance of power and dissymmetry in promoting participative knowledge and change in action research. Based on the analysis of two action research cases, the paper builds its argument by analyzing two key aspects: the construction of the action research setting and its maintenance during the process. It does so by highlighting the decisions assumed with respect to the relationship between researchers and participants and with respect to power issues. The findings indicate that promoting a functional dissymmetry in internal relationships allows distribution of the necessary types of power that make the participants use their authority and knowledge to invest in change. Thus, the distributed leadership is essential every time an organization needs to create a realistic and workable change of roles and responsibilities inside its boundaries. The article discusses some key factors in employing dissymmetry for sustained learning and knowledge-sharing.     

Glucose sensing by POMC neurons regulates glucose homeostasis and is impaired in obesity

A subset of neurons in the brain, known as 'glucose-excited' neurons, depolarize and increase their firing rate in response to increases in extracellular glucose. Similar to insulin secretion by pancreatic beta-cells, glucose excitation of neurons is driven by ATP-mediated closure of ATP-sensitive potassium (K(ATP)) channels. Although beta-cell-like glucose sensing in neurons is well established, its physiological relevance and contribution to disease states such as type 2 diabetes remain unknown. To address these issues, we disrupted glucose sensing in glucose-excited pro-opiomelanocortin (POMC) neurons via transgenic expression of a mutant Kir6.2 subunit (encoded by the Kcnj11 gene) that prevents ATP-mediated closure of K(ATP) channels. Here we show that this genetic manipulation impaired the whole-body response to a systemic glucose load, demonstrating a role for glucose sensing by POMC neurons in the overall physiological control of blood glucose. We also found that glucose sensing by POMC neurons became defective in obese mice on a high-fat diet, suggesting that loss of glucose sensing by neurons has a role in the development of type 2 diabetes. The mechanism for obesity-induced loss of glucose sensing in POMC neurons involves uncoupling protein 2 (UCP2), a mitochondrial protein that impairs glucose-stimulated ATP production. UCP2 negatively regulates glucose sensing in POMC neurons. We found that genetic deletion of Ucp2 prevents obesity-induced loss of glucose sensing, and that acute pharmacological inhibition of UCP2 reverses loss of glucose sensing. We conclude that obesity-induced, UCP2-mediated loss of glucose sensing in glucose-excited neurons might have a pathogenic role in the development of type 2 diabetes.     

Low-energy acoustic plasmons at metal surfaces

Nearly two-dimensional (2D) metallic systems formed in charge inversion layers and artificial layered materials permit the existence of low-energy collective excitations, called 2D plasmons, which are not found in a three-dimensional (3D) metal. These excitations have caused considerable interest because their low energy allows them to participate in many dynamical processes involving electrons and phonons, and because they might mediate the formation of Cooper pairs in high-transition-temperature superconductors. Metals often support electronic states that are confined to the surface, forming a nearly 2D electron-density layer. However, it was argued that these systems could not support low-energy collective excitations because they would be screened out by the underlying bulk electrons. Rather, metallic surfaces should support only conventional surface plasmons-higher-energy modes that depend only on the electron density. Surface plasmons have important applications in microscopy and sub-wavelength optics, but have no relevance to the low-energy dynamics. Here we show that, in contrast to expectations, a low-energy collective excitation mode can be found on bare metal surfaces. The mode has an acoustic (linear) dispersion, different to the dependence of a 2D plasmon, and was observed on Be(0001) using angle-resolved electron energy loss spectroscopy. First-principles calculations show that it is caused by the coexistence of a partially occupied quasi-2D surface-state band with the underlying 3D bulk electron continuum and also that the non-local character of the dielectric function prevents it from being screened out by the 3D states. The acoustic plasmon reported here has a very general character and should be present on many metal surfaces. Furthermore, its acoustic dispersion allows the confinement of light on small surface areas and in a broad frequency range, which is relevant for nano-optics and photonics applications.     

A second generation human haplotype map of over 3.1 million SNPs

We describe the Phase II HapMap, which characterizes over 3.1 million human single nucleotide polymorphisms (SNPs) genotyped in 270 individuals from four geographically diverse populations and includes 25-35% of common SNP variation in the populations surveyed. The map is estimated to capture untyped common variation with an average maximum r2 of between 0.9 and 0.96 depending on population. We demonstrate that the current generation of commercial genome-wide genotyping products captures common Phase II SNPs with an average maximum r2 of up to 0.8 in African and up to 0.95 in non-African populations, and that potential gains in power in association studies can be obtained through imputation. These data also reveal novel aspects of the structure of linkage disequilibrium. We show that 10-30% of pairs of individuals within a population share at least one region of extended genetic identity arising from recent ancestry and that up to 1% of all common variants are untaggable, primarily because they lie within recombination hotspots. We show that recombination rates vary systematically around genes and between genes of different function. Finally, we demonstrate increased differentiation at non-synonymous, compared to synonymous, SNPs, resulting from systematic differences in the strength or efficacy of natural selection between populations.     

Genome-wide detection and characterization of positive selection in human populations

With the advent of dense maps of human genetic variation, it is now possible to detect positive natural selection across the human genome. Here we report an analysis of over 3 million polymorphisms from the International HapMap Project Phase 2 (HapMap2). We used 'long-range haplotype' methods, which were developed to identify alleles segregating in a population that have undergone recent selection, and we also developed new methods that are based on cross-population comparisons to discover alleles that have swept to near-fixation within a population. The analysis reveals more than 300 strong candidate regions. Focusing on the strongest 22 regions, we develop a heuristic for scrutinizing these regions to identify candidate targets of selection. In a complementary analysis, we identify 26 non-synonymous, coding, single nucleotide polymorphisms showing regional evidence of positive selection. Examination of these candidates highlights three cases in which two genes in a common biological process have apparently undergone positive selection in the same population:LARGE and DMD, both related to infection by the Lassa virus, in West Africa;SLC24A5 and SLC45A2, both involved in skin pigmentation, in Europe; and EDAR and EDA2R, both involved in development of hair follicles, in Asia.