The Genetic Legacy of Religious Diversity and Intolerance: Paternal Lineages of Christians, Jews, and Muslims in the Iberian Peninsula

Most studies of European genetic diversity have focused on large-scale variation and interpretations based on events in prehistory, but migrations and invasions in historical times could also have had profound effects on the genetic landscape. The Iberian Peninsula provides a suitable region for examination of the demographic impact of such recent events, because its complex recent history has involved the long-term residence of two very different populations with distinct geographical origins and their own particular cultural and religious characteristics—North African Muslims and Sephardic Jews. To address this issue, we analyzed Y chromosome haplotypes, which provide the necessary phylogeographic resolution, in 1140 males from the Iberian Peninsula and Balearic Islands. Admixture analysis based on binary and Y-STR haplotypes indicates a high mean proportion of ancestry from North African (10.6%) and Sephardic Jewish (19.8%) sources. Despite alternative possible sources for lineages ascribed a Sephardic Jewish origin, these proportions attest to a high level of religious conversion (whether voluntary or enforced), driven by historical episodes of social and religious intolerance, that ultimately led to the integration of descendants. In agreement with the historical record, analysis of haplotype sharing and diversity within specific haplogroups suggests that the Sephardic Jewish component is the more ancient. The geographical distribution of North African ancestry in the peninsula does not reflect the initial colonization and subsequent withdrawal and is likely to result from later enforced population movement—more marked in some regions than in others—plus the effects of genetic drift.     

Somatic awareness in the clinical care of patients with body distress symptoms

The purpose of this paper is to provide primary care physicians and medical specialists with an experiential psychosomatic framework for understanding patients with body distress symptoms. The framework relies on somatic awareness, a normal part of consciousness, to resolve the dualism inherent in conventional multidisciplinary approaches. Somatic awareness represents a guiding healing heuristic which acknowledges the validity of the patient's physical symptoms and uses body sensations to identify the psychological, physiological, and social factors needed for symptom self-regulation. The experiential approach is based on psychobiologic concepts which include bodily distress disorder, central sensitization, dysfunctional breathing, and contextual nature of mood.     

Fluoride-inhibited calcium ATPase of sarcoplasmic reticulum. Magnesium and fluoride stoichiometry.

The sarcoplasmic reticulum (SR) CaATPase is inactivated by fluoride in the presence of magnesium (Murphy, A. J., and Coll, R. J. (1992) J. Biol. Chem. 267, 5229-5235). The inactive complex is very stable and can be isolated free of other components by 48 h of dialysis at 4 degrees C (Murphy, A. J., and Coll, R. J. (1992) J. Biol. Chem. 267, 16990-16994). In this study, we used a fluoride-specific electrode to determine that the amount of tightly bound fluoride in the complex was 9.4 +/- 2 nmol mg-1 SR protein. The rate constant of inactivation was very similar to the rate constant of fluoride incorporation and varied directly as the square of the fluoride concentration. Luminal Ca2+ accelerated reactivation of the inhibited enzyme, and the rate constants of activity regain and fluoride release were very similar. Although required for inhibition, added magnesium did not accelerate reactivation. Analysis for magnesium using antipyrylazo III of the inhibited enzyme showed 4.1 +/- 0.4 nmol mg-1 SR protein. As there is much evidence in the literature supportive of an estimate of calcium pumps equal to approximately 4-5 nmol mg-1 SR protein, our results indicate that each inhibited enzyme contains two tightly bound fluorides and one tightly bound magnesium.     

How costly is clutch formation in the Audouin's Gull Larus audouinii?

During the Audouin's Gull's breeding season at the Ebro Delta in 1993, 24 fresh eggs from eight three-egg clutches (modal clutch-size) were collected at the peak of the laying period. Eggs were processed to obtain formalin-fixed yolks, which were halved and stained using the potassium dichromate method. Digitized images of the yolks were examined to assess the daily rates of yolk deposition. We used these data in combination with egg compositional analysis to build a model of energy demands during the formation of an average clutch in Audouin's Gull. To show how the different parameters of clutch formation affect the daily energy investment peak, we performed a simulation analysis in which the rapid yolk development (RYD) period, the follicle triggering interval (FTI), the laying interval (LI) and the albumen synthesis period (ASP) were allowed to vary simultaneously. In our sample, the mean RYD period was seven days with a range from six to eight days. There were no significant differences in yolk volume among eggs in a clutch, but albumen volume was significantly smaller in third eggs. According to our model the albumen synthesis of the a-egg coincides with the energy demand peak for clutch formation. This peak represents an increase by ca. 42% in female energy requirements. Values obtained from the simulation analysis showed that only the ASP of the a-egg and the RYD durations of the second and third follicles produced noticeable reductions in peak energy investment. We predict that in gulls, whose laying intervals seem to be kept constant, significant increases of the durations of the RYD periods of second and third eggs, or even significant reductions of yolk size of these eggs, may operate simultaneously to match the energy demands during clutch formation to the prevailing food conditions.     

Population Level Inference for Multivariate MEG Analysis

Multivariate analysis is a very general and powerful technique for analysing Magnetoencephalography (MEG) data. An outstanding problem however is how to make inferences that are consistent over a group of subjects as to whether there are condition-specific differences in data features, and what are those features that maximise these differences. Here we propose a solution based on Canonical Variates Analysis (CVA) model scoring at the subject level and random effects Bayesian model selection at the group level. We apply this approach to beamformer reconstructed MEG data in source space. CVA estimates those multivariate patterns of activation that correlate most highly with the experimental design; the order of a CVA model is then determined by the number of significant canonical vectors. Random effects Bayesian model comparison then provides machinery for inferring the optimal order over the group of subjects. Absence of a multivariate dependence is indicated by the null model being the most likely. This approach can also be applied to CVA models with a fixed number of canonical vectors but supplied with different feature sets. We illustrate the method by identifying feature sets based on variable-dimension MEG power spectra in the primary visual cortex and fusiform gyrus that are maximally discriminative of data epochs before versus after visual stimulation.     

Note Onset Deviations as Musical Piece Signatures

A competent interpretation of a musical composition presents several non-explicit departures from the written score. Timing variations are perhaps the most important ones: they are fundamental for expressive performance and a key ingredient for conferring a human-like quality to machine-based music renditions. However, the nature of such variations is still an open research question, with diverse theories that indicate a multi-dimensional phenomenon. In the present study, we consider event-shift timing variations and show that sequences of note onset deviations are robust and reliable predictors of the musical piece being played, irrespective of the performer. In fact, our results suggest that only a few consecutive onset deviations are already enough to identify a musical composition with statistically significant accuracy. We consider a mid-size collection of commercial recordings of classical guitar pieces and follow a quantitative approach based on the combination of standard statistical tools and machine learning techniques with the semi-automatic estimation of onset deviations. Besides the reported results, we believe that the considered materials and the methodology followed widen the testing ground for studying musical timing and could open new perspectives in related research fields.