Mechanisms of synchronization and pattern formation in a lattice of pulse-coupled oscillators

We analyze the physical mechanisms leading either to synchronization or to the formation of spatiotemporal patterns in a lattice model of pulse-coupled oscillators. In order to make the system tractable from a mathematical point of view we study a one-dimensional ring with unidirectional coupling. In such a situation, exact results concerning the stability of the fixed of the dynamic evolution of the lattice can be obtained. Furthermore, we show that this stability is the responsible for the different behaviors.

Evolution under monogamy feminizes gene expression in Drosophila melanogaster.

Many genes have evolved sexually dimorphic expression as a consequence of divergent selection on males and females. However, because the sexes share a genome, the extent to which evolution can shape gene expression independently in each sex is controversial. Here, we use experimental evolution to reveal suboptimal sex-specific expression for much of the genome. By enforcing a monogamous mating system in populations of Drosophila melanogaster for over 100 generations, we eliminated major components of selection on males: female choice and male-male competition. If gene expression is subject to sexually antagonistic selection, relaxed selection on males should cause evolution towards female optima. Monogamous males and females show this pattern of feminization in both the whole-body and head transcriptomes. Genes with male-biased expression patterns evolved decreased expression under monogamy, while genes with female-biased expression evolved increased expression, relative to polygamous populations. Our results demonstrate persistent and widespread evolutionary tension between male and female adaptation.

A clinical pattern-based etiological diagnostic strategy for sensory neuronopathies: a French collaborative study.

Sensory neuronopathies (SNNs) encompass paraneoplastic, infectious, dysimmune, toxic, inherited, and idiopathic disorders. Recently described diagnostic criteria allow SNN to be differentiated from other forms of sensory neuropathy, but there is no validated strategy based on routine clinical investigations for the etiological diagnosis of SNN. In a multicenter study, the clinical, biological, and electrophysiological characteristics of 148 patients with SNN were analyzed. Multiple correspondence analysis and logistic regression were used to identify patterns differentiating between forms of SNNs with different etiologies. Models were constructed using a study population of 88 patients and checked using a test population of 60 cases. Four patterns were identified. Pattern A, with an acute or subacute onset in the four limbs or arms, early pain, and frequently affecting males over 60 years of age, identified mainly paraneoplastic, toxic, and infectious SNN. Pattern B identified patients with progressive SNN and was divided into patterns C and D, the former corresponding to patients with inherited or slowly progressive idiopathic SNN with severe ataxia and electrophysiological abnormalities and the latter to patients with idiopathic, dysimmune, and sometimes paraneoplastic SNN with a more rapid course than in pattern C. The diagnostic strategy based on these patterns correctly identified 84/88 and 58/60 patients in the study and test populations, respectively.

Early co-occurrence of a neurologic-psychiatric disease pattern in Niemann-Pick type C disease: a retrospective Swiss cohort study.

BackgroundNiemann-Pick disease type C (NP-C) is a rare autosomal recessive disorder of lysosomal cholesterol transport. The objective of this retrospective cohort study was to critically analyze the onset and time course of symptoms, and the clinical diagnostic work-up in the Swiss NP-C cohort.MethodsClinical, biochemical and genetic data were assessed for 14 patients derived from 9 families diagnosed with NP-C between 1994 and 2013. We retrospectively evaluated diagnostic delays and period prevalence rates for neurological, psychiatric and visceral symptoms associated with NP-C disease. The NP-C suspicion index was calculated for the time of neurological disease onset and the time of diagnosis.ResultsThe shortest median diagnostic delay was noted for vertical supranuclear gaze palsy (2y). Ataxia, dysarthria, dysphagia, spasticity, cataplexy, seizures and cognitive decline displayed similar median diagnostic delays (4¿5y). The longest median diagnostic delay was associated with hepatosplenomegaly (15y). Highest period prevalence rates were noted for ataxia, dysarthria, vertical supranuclear gaze palsy and cognitive decline. The NP-C suspicion index revealed a median score of 81 points in nine patients at the time of neurological disease onset which is highly suspicious for NP-C disease. At the time of diagnosis, the score increased to 206 points.ConclusionA neurologic-psychiatric disease pattern represents the most characteristic clinical manifestation of NP-C and occurs early in the disease course. Visceral manifestation such as isolated hepatosplenomegaly often fails recognition and thus highlights the importance of a work-up for lysosomal storage disorders. The NP-C suspicion index emphasizes the importance of a multisystem evaluation, but seems to be weak in monosymptomatic and infantile NP-C patients.

Evidence for catabolic pathway of propionate metabolism in CNS: expression pattern of methylmalonyl-CoA mutase and propionyl-CoA carboxylase alpha-subunit in developing and adult rat brain.

Methylmalonyl-CoA mutase (MCM) and propionyl-CoA carboxylase (PCC) are the key enzymes of the catabolic pathway of propionate metabolism and are mainly expressed in liver, kidney and heart. Deficiency of these enzymes leads to two classical organic acidurias: methylmalonic and propionic aciduria. Patients with these diseases suffer from a whole spectrum of neurological manifestations that are limiting their quality of life. Current treatment does not seem to effectively prevent neurological deterioration and pathophysiological mechanisms are poorly understood. In this article we show evidence for the expression of the catabolic pathway of propionate metabolism in the developing and adult rat CNS. Both, MCM and PCC enzymes are co-expressed in neurons and found in all regions of the CNS. Disease-specific metabolites such as methylmalonate, propionyl-CoA and 2-methylcitrate could thus be formed autonomously in the CNS and contribute to the pathophysiological mechanisms of neurotoxicity. In rat embryos (E15.5 and E18.5), MCM and PCC show a much higher expression level in the entire CNS than in the liver, suggesting a different, but important function of this pathway during brain development.

A proteomics approach to decipher the molecular nature of planarian stem cells.

Background In recent years, planaria have emerged as an important model system for research into stem cells and regeneration. Attention is focused on their unique stem cells, the neoblasts, which can differentiate into any cell type present in the adult organism. Sequencing of the Schmidtea mediterranea genome and some expressed sequence tag projects have generated extensive data on the genetic profile of these cells. However, little information is available on their protein dynamics. Results We developed a proteomic strategy to identify neoblast-specific proteins. Here we describe the method and discuss the results in comparison to the genomic high-throughput analyses carried out in planaria and to proteomic studies using other stem cell systems. We also show functional data for some of the candidate genes selected in our proteomic approach. Conclusions We have developed an accurate and reliable mass-spectra-based proteomics approach to complement previous genomic studies and to further achieve a more accurate understanding and description of the molecular and cellular processes related to the neoblasts.

Comparative genomics of the odorant-binding and chemosensory protein gene families across the arthropoda: origin and evolutionary history of the chemosensory system

Chemoreception is a biological process essential for the survival of animals, as it allows the recognition of important volatile cues for the detection of food, egg-laying substrates, mates or predators, among other purposes. Furthermore, its role in pheromone detection may contribute to evolutionary processes such as reproductive isolation and speciation. This key role in several vital biological processes makes chemoreception a particularly interesting system for studying the role of natural selection in molecular adaptation. Two major gene families are involved in the perireceptor events of the chemosensory system: the odorant-binding protein (OBP) and chemosensory protein (CSP) families. Here, we have conducted an exhaustive comparative genomic analysis of these gene families in twenty Arthropoda species. We show that the evolution of the OBP and CSP gene families is highly dynamic, with a high number of gains and losses of genes, pseudogenes and independent origins of subfamilies. Taken together, our data clearly support the birth-and-death model for the evolution of these gene families with an overall high gene-turnover rate. Moreover, we show that the genome organization of the two families is significantly more clustered than expected by chance and, more important, that this pattern appears to be actively maintained across the Drosophila phylogeny. Finally, we suggest the homologous nature of the OBP and CSP gene families, dating back their MRCA (most recent common ancestor) to 380¿420 Mya, and we propose a scenario for the origin and diversification of these families.

Apprentissage automatique de la morphologie : le cas des structures racine-schème

RÉSUMÉ Cette thèse porte sur le développement de méthodes algorithmiques pour découvrir automatiquement la structure morphologique des mots d'un corpus. On considère en particulier le cas des langues s'approchant du type introflexionnel, comme l'arabe ou l'hébreu. La tradition linguistique décrit la morphologie de ces langues en termes d'unités discontinues : les racines consonantiques et les schèmes vocaliques. Ce genre de structure constitue un défi pour les systèmes actuels d'apprentissage automatique, qui opèrent généralement avec des unités continues. La stratégie adoptée ici consiste à traiter le problème comme une séquence de deux sous-problèmes. Le premier est d'ordre phonologique : il s'agit de diviser les symboles (phonèmes, lettres) du corpus en deux groupes correspondant autant que possible aux consonnes et voyelles phonétiques. Le second est de nature morphologique et repose sur les résultats du premier : il s'agit d'établir l'inventaire des racines et schèmes du corpus et de déterminer leurs règles de combinaison. On examine la portée et les limites d'une approche basée sur deux hypothèses : (i) la distinction entre consonnes et voyelles peut être inférée sur la base de leur tendance à alterner dans la chaîne parlée; (ii) les racines et les schèmes peuvent être identifiés respectivement aux séquences de consonnes et voyelles découvertes précédemment. L'algorithme proposé utilise une méthode purement distributionnelle pour partitionner les symboles du corpus. Puis il applique des principes analogiques pour identifier un ensemble de candidats sérieux au titre de racine ou de schème, et pour élargir progressivement cet ensemble. Cette extension est soumise à une procédure d'évaluation basée sur le principe de la longueur de description minimale, dans- l'esprit de LINGUISTICA (Goldsmith, 2001). L'algorithme est implémenté sous la forme d'un programme informatique nommé ARABICA, et évalué sur un corpus de noms arabes, du point de vue de sa capacité à décrire le système du pluriel. Cette étude montre que des structures linguistiques complexes peuvent être découvertes en ne faisant qu'un minimum d'hypothèses a priori sur les phénomènes considérés. Elle illustre la synergie possible entre des mécanismes d'apprentissage portant sur des niveaux de description linguistique distincts, et cherche à déterminer quand et pourquoi cette coopération échoue. Elle conclut que la tension entre l'universalité de la distinction consonnes-voyelles et la spécificité de la structuration racine-schème est cruciale pour expliquer les forces et les faiblesses d'une telle approche. ABSTRACT This dissertation is concerned with the development of algorithmic methods for the unsupervised learning of natural language morphology, using a symbolically transcribed wordlist. It focuses on the case of languages approaching the introflectional type, such as Arabic or Hebrew. The morphology of such languages is traditionally described in terms of discontinuous units: consonantal roots and vocalic patterns. Inferring this kind of structure is a challenging task for current unsupervised learning systems, which generally operate with continuous units. In this study, the problem of learning root-and-pattern morphology is divided into a phonological and a morphological subproblem. The phonological component of the analysis seeks to partition the symbols of a corpus (phonemes, letters) into two subsets that correspond well with the phonetic definition of consonants and vowels; building around this result, the morphological component attempts to establish the list of roots and patterns in the corpus, and to infer the rules that govern their combinations. We assess the extent to which this can be done on the basis of two hypotheses: (i) the distinction between consonants and vowels can be learned by observing their tendency to alternate in speech; (ii) roots and patterns can be identified as sequences of the previously discovered consonants and vowels respectively. The proposed algorithm uses a purely distributional method for partitioning symbols. Then it applies analogical principles to identify a preliminary set of reliable roots and patterns, and gradually enlarge it. This extension process is guided by an evaluation procedure based on the minimum description length principle, in line with the approach to morphological learning embodied in LINGUISTICA (Goldsmith, 2001). The algorithm is implemented as a computer program named ARABICA; it is evaluated with regard to its ability to account for the system of plural formation in a corpus of Arabic nouns. This thesis shows that complex linguistic structures can be discovered without recourse to a rich set of a priori hypotheses about the phenomena under consideration. It illustrates the possible synergy between learning mechanisms operating at distinct levels of linguistic description, and attempts to determine where and why such a cooperation fails. It concludes that the tension between the universality of the consonant-vowel distinction and the specificity of root-and-pattern structure is crucial for understanding the advantages and weaknesses of this approach.

Hundreds of variants clustered in genomic loci and biological pathways affect human height.

Most common human traits and diseases have a polygenic pattern of inheritance: DNA sequence variants at many genetic loci influence the phenotype. Genome-wide association (GWA) studies have identified more than 600 variants associated with human traits, but these typically explain small fractions of phenotypic variation, raising questions about the use of further studies. Here, using 183,727 individuals, we show that hundreds of genetic variants, in at least 180 loci, influence adult height, a highly heritable and classic polygenic trait. The large number of loci reveals patterns with important implications for genetic studies of common human diseases and traits. First, the 180 loci are not random, but instead are enriched for genes that are connected in biological pathways (P = 0.016) and that underlie skeletal growth defects (P < 0.001). Second, the likely causal gene is often located near the most strongly associated variant: in 13 of 21 loci containing a known skeletal growth gene, that gene was closest to the associated variant. Third, at least 19 loci have multiple independently associated variants, suggesting that allelic heterogeneity is a frequent feature of polygenic traits, that comprehensive explorations of already-discovered loci should discover additional variants and that an appreciable fraction of associated loci may have been identified. Fourth, associated variants are enriched for likely functional effects on genes, being over-represented among variants that alter amino-acid structure of proteins and expression levels of nearby genes. Our data explain approximately 10% of the phenotypic variation in height, and we estimate that unidentified common variants of similar effect sizes would increase this figure to approximately 16% of phenotypic variation (approximately 20% of heritable variation). Although additional approaches are needed to dissect the genetic architecture of polygenic human traits fully, our findings indicate that GWA studies can identify large numbers of loci that implicate biologically relevant genes and pathways.

Cerebral infarction in diabetes: Clinical pattern, stroke subtypes,and predictors of in-hospital mortality

Background: To compare the characteristics and prognostic features of ischemic stroke in patients with diabetes and without diabetes, and to determine the independent predictors of in-hospital mortality in people with diabetes and ischemic stroke.Methods: Diabetes was diagnosed in 393 (21.3%) of 1,840 consecutive patients with cerebral infarction included in a prospective stroke registry over a 12-year period. Demographic characteristics, cardiovascular risk factors, clinical events, stroke subtypes, neuroimaging data, and outcome in ischemic stroke patients with and without diabetes were compared. Predictors of in-hospital mortality in diabetic patients with ischemic stroke were assessed by multivariate analysis. Results: People with diabetes compared to people without diabetes presented more frequently atherothrombotic stroke (41.2% vs 27%) and lacunar infarction (35.1% vs 23.9%) (P < 0.01). The in-hospital mortality in ischemic stroke patients with diabetes was 12.5% and 14.6% in those without (P = NS). Ischemic heart disease, hyperlipidemia, subacute onset, 85 years old or more, atherothrombotic and lacunar infarcts, and thalamic topography were independently associated with ischemic stroke in patients with diabetes, whereas predictors of in-hospital mortality included the patient's age, decreased consciousness, chronic nephropathy, congestive heart failure and atrial fibrillation. Conclusion: Ischemic stroke in people with diabetes showed a different clinical pattern from those without diabetes, with atherothrombotic stroke and lacunar infarcts being more frequent. Clinical factors indicative of the severity of ischemic stroke available at onset have a predominant influence upon in-hospital mortality and may help clinicians to assess prognosis more accurately.

Serum glycodelin pattern during the menstrual cycle in healthy young women.

OBJECTIVE: Glycodelin (PP14) is produced by the epithelium of the endometrium and its determination in the serum is used for functional evaluation of this tissue. Given the complex regulation and the combined contraceptive and immunosuppressive roles of glycodelin, the current lack of normal values for its serum concentration in the physiological menstrual cycle, derived from a large sample number, is a problem. We have therefore established reference values from over 600 sera. DESIGN: Retrospective study using banked serum samples. SETTING: University hospital. METHODS: Measurement of blood samples daily or every second day during one full cycle. MAIN OUTCOME MEASURES: Serum concentrations of glycodelin and normal values for every such one- or two-day interval were calculated. Late luteal phase glycodelin levels were compared with ovarian hormones. Follicular phase levels were compared with stimulated cycles from patients undergoing in vitro fertilization. RESULTS: Glycodelin concentrations were low around ovulation. Highest levels were observed at the end of the luteal phase; the glycodelin serum peak was reached 6-8 days after the one for progesterone. Late luteal glycodelin levels correlated negatively with the body mass index and positively with the progesterone level earlier in the secretory (mid-luteal) phase in the same woman. No associations with other ovarian hormones were observed. Follicular phase glycodelin levels were higher in the spontaneous than in the in vitro fertilization cycles. CONCLUSIONS: Normal values taken at two- or one-day intervals demonstrate the very late appearance of high serum glycodelin levels during the physiological menstrual cycle and their correlation with progesterone occurring earlier in the cycle.