Biological evidence supports an early and complex emergence of the Isthmus of Panama.

The linking of North and South America by the Isthmus of Panama had major impacts on global climate, oceanic and atmospheric currents, and biodiversity, yet the timing of this critical event remains contentious. The Isthmus is traditionally understood to have fully closed by ca. 3.5 million years ago (Ma), and this date has been used as a benchmark for oceanographic, climatic, and evolutionary research, but recent evidence suggests a more complex geological formation. Here, we analyze both molecular and fossil data to evaluate the tempo of biotic exchange across the Americas in light of geological evidence. We demonstrate significant waves of dispersal of terrestrial organisms at approximately ca. 20 and 6 Ma and corresponding events separating marine organisms in the Atlantic and Pacific oceans at ca. 23 and 7 Ma. The direction of dispersal and their rates were symmetrical until the last ca. 6 Ma, when northern migration of South American lineages increased significantly. Variability among taxa in their timing of dispersal or vicariance across the Isthmus is not explained by the ecological factors tested in these analyses, including biome type, dispersal ability, and elevation preference. Migration was therefore not generally regulated by intrinsic traits but more likely reflects the presence of emergent terrain several millions of years earlier than commonly assumed. These results indicate that the dramatic biotic turnover associated with the Great American Biotic Interchange was a long and complex process that began as early as the Oligocene-Miocene transition.

Evolutionary games on complex networks : the emergence and maintenance of cooperation

Abstract The object of game theory lies in the analysis of situations where different social actors have conflicting requirements and where their individual decisions will all influence the global outcome. In this framework, several games have been invented to capture the essence of various dilemmas encountered in many common important socio-economic situations. Even though these games often succeed in helping us understand human or animal behavior in interactive settings, some experiments have shown that people tend to cooperate with each other in situations for which classical game theory strongly recommends them to do the exact opposite. Several mechanisms have been invoked to try to explain the emergence of this unexpected cooperative attitude. Among them, repeated interaction, reputation, and belonging to a recognizable group have often been mentioned. However, the work of Nowak and May (1992) showed that the simple fact of arranging the players according to a spatial structure and only allowing them to interact with their immediate neighbors is sufficient to sustain a certain amount of cooperation even when the game is played anonymously and without repetition. Nowak and May's study and much of the following work was based on regular structures such as two-dimensional grids. Axelrod et al. (2002) showed that by randomizing the choice of neighbors, i.e. by actually giving up a strictly local geographical structure, cooperation can still emerge, provided that the interaction patterns remain stable in time. This is a first step towards a social network structure. However, following pioneering work by sociologists in the sixties such as that of Milgram (1967), in the last few years it has become apparent that many social and biological interaction networks, and even some technological networks, have particular, and partly unexpected, properties that set them apart from regular or random graphs. Among other things, they usually display broad degree distributions, and show small-world topological structure. Roughly speaking, a small-world graph is a network where any individual is relatively close, in terms of social ties, to any other individual, a property also found in random graphs but not in regular lattices. However, in contrast with random graphs, small-world networks also have a certain amount of local structure, as measured, for instance, by a quantity called the clustering coefficient. In the same vein, many real conflicting situations in economy and sociology are not well described neither by a fixed geographical position of the individuals in a regular lattice, nor by a random graph. Furthermore, it is a known fact that network structure can highly influence dynamical phenomena such as the way diseases spread across a population and ideas or information get transmitted. Therefore, in the last decade, research attention has naturally shifted from random and regular graphs towards better models of social interaction structures. The primary goal of this work is to discover whether or not the underlying graph structure of real social networks could give explanations as to why one finds higher levels of cooperation in populations of human beings or animals than what is prescribed by classical game theory. To meet this objective, I start by thoroughly studying a real scientific coauthorship network and showing how it differs from biological or technological networks using divers statistical measurements. Furthermore, I extract and describe its community structure taking into account the intensity of a collaboration. Finally, I investigate the temporal evolution of the network, from its inception to its state at the time of the study in 2006, suggesting also an effective view of it as opposed to a historical one. Thereafter, I combine evolutionary game theory with several network models along with the studied coauthorship network in order to highlight which specific network properties foster cooperation and shed some light on the various mechanisms responsible for the maintenance of this same cooperation. I point out the fact that, to resist defection, cooperators take advantage, whenever possible, of the degree-heterogeneity of social networks and their underlying community structure. Finally, I show that cooperation level and stability depend not only on the game played, but also on the evolutionary dynamic rules used and the individual payoff calculations. Synopsis Le but de la théorie des jeux réside dans l'analyse de situations dans lesquelles différents acteurs sociaux, avec des objectifs souvent conflictuels, doivent individuellement prendre des décisions qui influenceront toutes le résultat global. Dans ce cadre, plusieurs jeux ont été inventés afin de saisir l'essence de divers dilemmes rencontrés dans d'importantes situations socio-économiques. Bien que ces jeux nous permettent souvent de comprendre le comportement d'êtres humains ou d'animaux en interactions, des expériences ont montré que les individus ont parfois tendance à coopérer dans des situations pour lesquelles la théorie classique des jeux prescrit de faire le contraire. Plusieurs mécanismes ont été invoqués pour tenter d'expliquer l'émergence de ce comportement coopératif inattendu. Parmi ceux-ci, la répétition des interactions, la réputation ou encore l'appartenance à des groupes reconnaissables ont souvent été mentionnés. Toutefois, les travaux de Nowak et May (1992) ont montré que le simple fait de disposer les joueurs selon une structure spatiale en leur permettant d'interagir uniquement avec leurs voisins directs est suffisant pour maintenir un certain niveau de coopération même si le jeu est joué de manière anonyme et sans répétitions. L'étude de Nowak et May, ainsi qu'un nombre substantiel de travaux qui ont suivi, étaient basés sur des structures régulières telles que des grilles à deux dimensions. Axelrod et al. (2002) ont montré qu'en randomisant le choix des voisins, i.e. en abandonnant une localisation géographique stricte, la coopération peut malgré tout émerger, pour autant que les schémas d'interactions restent stables au cours du temps. Ceci est un premier pas en direction d'une structure de réseau social. Toutefois, suite aux travaux précurseurs de sociologues des années soixante, tels que ceux de Milgram (1967), il est devenu clair ces dernières années qu'une grande partie des réseaux d'interactions sociaux et biologiques, et même quelques réseaux technologiques, possèdent des propriétés particulières, et partiellement inattendues, qui les distinguent de graphes réguliers ou aléatoires. Entre autres, ils affichent en général une distribution du degré relativement large ainsi qu'une structure de "petit-monde". Grossièrement parlant, un graphe "petit-monde" est un réseau où tout individu se trouve relativement près de tout autre individu en termes de distance sociale, une propriété également présente dans les graphes aléatoires mais absente des grilles régulières. Par contre, les réseaux "petit-monde" ont, contrairement aux graphes aléatoires, une certaine structure de localité, mesurée par exemple par une quantité appelée le "coefficient de clustering". Dans le même esprit, plusieurs situations réelles de conflit en économie et sociologie ne sont pas bien décrites ni par des positions géographiquement fixes des individus en grilles régulières, ni par des graphes aléatoires. De plus, il est bien connu que la structure même d'un réseau peut passablement influencer des phénomènes dynamiques tels que la manière qu'a une maladie de se répandre à travers une population, ou encore la façon dont des idées ou une information s'y propagent. Ainsi, durant cette dernière décennie, l'attention de la recherche s'est tout naturellement déplacée des graphes aléatoires et réguliers vers de meilleurs modèles de structure d'interactions sociales. L'objectif principal de ce travail est de découvrir si la structure sous-jacente de graphe de vrais réseaux sociaux peut fournir des explications quant aux raisons pour lesquelles on trouve, chez certains groupes d'êtres humains ou d'animaux, des niveaux de coopération supérieurs à ce qui est prescrit par la théorie classique des jeux. Dans l'optique d'atteindre ce but, je commence par étudier un véritable réseau de collaborations scientifiques et, en utilisant diverses mesures statistiques, je mets en évidence la manière dont il diffère de réseaux biologiques ou technologiques. De plus, j'extrais et je décris sa structure de communautés en tenant compte de l'intensité d'une collaboration. Finalement, j'examine l'évolution temporelle du réseau depuis son origine jusqu'à son état en 2006, date à laquelle l'étude a été effectuée, en suggérant également une vue effective du réseau par opposition à une vue historique. Par la suite, je combine la théorie évolutionnaire des jeux avec des réseaux comprenant plusieurs modèles et le réseau de collaboration susmentionné, afin de déterminer les propriétés structurelles utiles à la promotion de la coopération et les mécanismes responsables du maintien de celle-ci. Je mets en évidence le fait que, pour ne pas succomber à la défection, les coopérateurs exploitent dans la mesure du possible l'hétérogénéité des réseaux sociaux en termes de degré ainsi que la structure de communautés sous-jacente de ces mêmes réseaux. Finalement, je montre que le niveau de coopération et sa stabilité dépendent non seulement du jeu joué, mais aussi des règles de la dynamique évolutionnaire utilisées et du calcul du bénéfice d'un individu.

Towards robust network based complex systems : from evolutionary cellular automata to biological models

Abstract Sitting between your past and your future doesn't mean you are in the present. Dakota Skye Complex systems science is an interdisciplinary field grouping under the same umbrella dynamical phenomena from social, natural or mathematical sciences. The emergence of a higher order organization or behavior, transcending that expected of the linear addition of the parts, is a key factor shared by all these systems. Most complex systems can be modeled as networks that represent the interactions amongst the system's components. In addition to the actual nature of the part's interactions, the intrinsic topological structure of underlying network is believed to play a crucial role in the remarkable emergent behaviors exhibited by the systems. Moreover, the topology is also a key a factor to explain the extraordinary flexibility and resilience to perturbations when applied to transmission and diffusion phenomena. In this work, we study the effect of different network structures on the performance and on the fault tolerance of systems in two different contexts. In the first part, we study cellular automata, which are a simple paradigm for distributed computation. Cellular automata are made of basic Boolean computational units, the cells; relying on simple rules and information from- the surrounding cells to perform a global task. The limited visibility of the cells can be modeled as a network, where interactions amongst cells are governed by an underlying structure, usually a regular one. In order to increase the performance of cellular automata, we chose to change its topology. We applied computational principles inspired by Darwinian evolution, called evolutionary algorithms, to alter the system's topological structure starting from either a regular or a random one. The outcome is remarkable, as the resulting topologies find themselves sharing properties of both regular and random network, and display similitudes Watts-Strogtz's small-world network found in social systems. Moreover, the performance and tolerance to probabilistic faults of our small-world like cellular automata surpasses that of regular ones. In the second part, we use the context of biological genetic regulatory networks and, in particular, Kauffman's random Boolean networks model. In some ways, this model is close to cellular automata, although is not expected to perform any task. Instead, it simulates the time-evolution of genetic regulation within living organisms under strict conditions. The original model, though very attractive by it's simplicity, suffered from important shortcomings unveiled by the recent advances in genetics and biology. We propose to use these new discoveries to improve the original model. Firstly, we have used artificial topologies believed to be closer to that of gene regulatory networks. We have also studied actual biological organisms, and used parts of their genetic regulatory networks in our models. Secondly, we have addressed the improbable full synchronicity of the event taking place on. Boolean networks and proposed a more biologically plausible cascading scheme. Finally, we tackled the actual Boolean functions of the model, i.e. the specifics of how genes activate according to the activity of upstream genes, and presented a new update function that takes into account the actual promoting and repressing effects of one gene on another. Our improved models demonstrate the expected, biologically sound, behavior of previous GRN model, yet with superior resistance to perturbations. We believe they are one step closer to the biological reality.

Dispersal (Entropy) and Recognition (Information) as Foundations of Emergence and Dissolvence

The objective of this essay is to reflect on a possible relation between entropy and emergence. A qualitative, relational approach is followed. We begin by highlighting that entropy includes the concept of dispersal, relevant to our enquiry. Emergence in complex systems arises from the coordinated behavior of their parts. Coordination in turn necessitates recognition between parts, i.e., information exchange. What will be argued here is that the scope of recognition processes between parts is increased when preceded by their dispersal, which multiplies the number of encounters and creates a richer potential for recognition. A process intrinsic to emergence is dissolvence (aka submergence or top-down constraints), which participates in the information-entropy interplay underlying the creation, evolution and breakdown of higher-level entities.

Proteomic and Metabolomic Analyses of Mitochondrial Complex I-deficient Mouse Model Generated by Spontaneous B2 Short Interspersed Nuclear Element (SINE) Insertion into NADH Dehydrogenase (Ubiquinone) Fe-S Protein 4 (Ndufs4) Gene.

Eukaryotic cells generate energy in the form of ATP, through a network of mitochondrial complexes and electron carriers known as the oxidative phosphorylation system. In mammals, mitochondrial complex I (CI) is the largest component of this system, comprising 45 different subunits encoded by mitochondrial and nuclear DNA. Humans diagnosed with mutations in the gene NDUFS4, encoding a nuclear DNA-encoded subunit of CI (NADH dehydrogenase ubiquinone Fe-S protein 4), typically suffer from Leigh syndrome, a neurodegenerative disease with onset in infancy or early childhood. Mitochondria from NDUFS4 patients usually lack detectable NDUFS4 protein and show a CI stability/assembly defect. Here, we describe a recessive mouse phenotype caused by the insertion of a transposable element into Ndufs4, identified by a novel combined linkage and expression analysis. Designated Ndufs4(fky), the mutation leads to aberrant transcript splicing and absence of NDUFS4 protein in all tissues tested of homozygous mice. Physical and behavioral symptoms displayed by Ndufs4(fky/fky) mice include temporary fur loss, growth retardation, unsteady gait, and abnormal body posture when suspended by the tail. Analysis of CI in Ndufs4(fky/fky) mice using blue native PAGE revealed the presence of a faster migrating crippled complex. This crippled CI was shown to lack subunits of the "N assembly module", which contains the NADH binding site, but contained two assembly factors not present in intact CI. Metabolomic analysis of the blood by tandem mass spectrometry showed increased hydroxyacylcarnitine species, implying that the CI defect leads to an imbalanced NADH/NAD(+) ratio that inhibits mitochondrial fatty acid β-oxidation.

3-T direct MR arthrography of the wrist: value of finger trap distraction to assess intrinsic ligament and triangular fibrocartilage complex tears.

PURPOSE: To determine the value of applying finger trap distraction during direct MR arthrography of the wrist to assess intrinsic ligament and triangular fibrocartilage complex (TFCC) tears. MATERIALS AND METHODS: Twenty consecutive patients were prospectively investigated by three-compartment wrist MR arthrography. Imaging was performed with 3-T scanners using a three-dimensional isotropic (0.4 mm) T1-weighted gradient-recalled echo sequence, with and without finger trap distraction (4 kg). In a blind and independent fashion, two musculoskeletal radiologists measured the width of the scapholunate (SL), lunotriquetral (LT) and ulna-TFC (UTFC) joint spaces. They evaluated the amount of contrast medium within these spaces using a four-point scale, and assessed SL, LT and TFCC tears, as well as the disruption of Gilula's carpal arcs. RESULTS: With finger trap distraction, both readers found a significant increase in width of the SL space (mean Δ = +0.1mm, p ≤ 0.040), and noticed more contrast medium therein (p ≤ 0.035). In contrast, the differences in width of the LT (mean Δ = +0.1 mm, p ≥ 0.057) and UTFC (mean Δ = 0mm, p ≥ 0.728) spaces, as well as the amount of contrast material within these spaces were not statistically significant (p = 0.607 and ≥ 0.157, respectively). Both readers detected more SL (Δ = +1, p = 0.157) and LT (Δ = +2, p = 0.223) tears, although statistical significance was not reached, and Gilula's carpal arcs were more frequently disrupted during finger trap distraction (Δ = +5, p = 0.025). CONCLUSION: The application of finger trap distraction during direct wrist MR arthrography may enhance both detection and characterisation of SL and LT ligament tears by widening the SL space and increasing the amount of contrast within the SL and LT joint spaces.

A simple genetic basis for complex social behaviour mediates widespread gene expression differences.

A remarkable social polymorphism is controlled by a single Mendelian factor in the fire ant Solenopsis invicta. A genomic element marked by the gene Gp-9 determines whether workers tolerate one or many fertile queens in their colony. Gp-9 was recently shown to be part of a supergene with two nonrecombining variants, SB and Sb. SB/SB and SB/Sb queens differ in how they initiate new colonies, and in many physiological traits, for example odour and maturation rate. To understand how a single genetic element can affect all these traits, we used a microarray to compare gene expression patterns between SB/SB and SB/Sb queens of three different age classes: 1-day-old unmated queens, 11-day-old unmated queens and mated, fully reproductive queens collected from mature field colonies. The number of genes that were differentially expressed between SB/SB and SB/Sb queens of the same age class was smallest in 1-day-old queens, maximal in 11-day-old queens and intermediate in reproductive queens. Gene ontology analysis showed that SB/SB queens upregulate reproductive genes faster than SB/Sb queens. For all age classes, genes inside the supergene were overrepresented among the differentially expressed genes. Consistent with the hypothesized greater number of transposons in the Sb supergene, 13 transposon genes were upregulated in SB/Sb queens. Viral genes were also upregulated in SB/Sb mature queens, consistent with the known greater parasite load in colonies headed by SB/Sb queens compared with colonies headed by SB/SB queens. Eighteen differentially expressed genes between reproductive queens were involved in chemical signalling. Our results suggest that many genes in the supergene are involved in regulating social organization and queen phenotypes in fire ants.

Rare genomic structural variants in complex disease: lessons from the replication of associations with obesity.

The limited ability of common variants to account for the genetic contribution to complex disease has prompted searches for rare variants of large effect, to partly explain the 'missing heritability'. Analyses of genome-wide genotyping data have identified genomic structural variants (GSVs) as a source of such rare causal variants. Recent studies have reported multiple GSV loci associated with risk of obesity. We attempted to replicate these associations by similar analysis of two familial-obesity case-control cohorts and a population cohort, and detected GSVs at 11 out of 18 loci, at frequencies similar to those previously reported. Based on their reported frequencies and effect sizes (OR≥25), we had sufficient statistical power to detect the large majority (80%) of genuine associations at these loci. However, only one obesity association was replicated. Deletion of a 220 kb region on chromosome 16p11.2 has a carrier population frequency of 2×10(-4) (95% confidence interval [9.6×10(-5)-3.1×10(-4)]); accounts overall for 0.5% [0.19%-0.82%] of severe childhood obesity cases (P = 3.8×10(-10); odds ratio = 25.0 [9.9-60.6]); and results in a mean body mass index (BMI) increase of 5.8 kg.m(-2) [1.8-10.3] in adults from the general population. We also attempted replication using BMI as a quantitative trait in our population cohort; associations with BMI at or near nominal significance were detected at two further loci near KIF2B and within FOXP2, but these did not survive correction for multiple testing. These findings emphasise several issues of importance when conducting rare GSV association, including the need for careful cohort selection and replication strategy, accurate GSV identification, and appropriate correction for multiple testing and/or control of false discovery rate. Moreover, they highlight the potential difficulty in replicating rare CNV associations across different populations. Nevertheless, we show that such studies are potentially valuable for the identification of variants making an appreciable contribution to complex disease.

Profiling of T-cell receptor signaling complex assembly in human CD4 T-lymphocytes using RP protein arrays.

The RP protein (RPP) array approach immobilizes minute amounts of cell lysates or tissue protein extracts as distinct microspots on NC-coated slide. Subsequent detection with specific antibodies allows multiplexed quantification of proteins and their modifications at a scale that is beyond what traditional techniques can achieve. Cellular functions are the result of the coordinated action of signaling proteins assembled in macromolecular complexes. These signaling complexes are highly dynamic structures that change their composition with time and space to adapt to cell environment. Their comprehensive analysis requires until now relatively large amounts of cells (>5 x 10(7)) due to their low abundance and breakdown during isolation procedure. In this study, we combined small scale affinity capture of the T-cell receptor (TCR) and RPP arrays to follow TCR signaling complex assembly in human ex vivo isolated CD4 T-cells. Using this strategy, we report specific recruitment of signaling components to the TCR complex upon T-cell activation in as few as 0.5 million of cells. Second- to fourth-order TCR interacting proteins were accurately quantified, making this strategy specially well-suited to the analysis of membrane-associated signaling complexes in limited amounts of cells or tissues, e.g., ex vivo isolated cells or clinical specimens.

The specificity of TRIM5 alpha-mediated restriction is influenced by its coiled-coil domain.

Retroviruses are both powerful evolutionary forces and dangerous threats to genome integrity. As such, they have imposed strong selective pressure on their hosts, notably triggering the emergence of restriction factors, such as TRIM5 alpha, that act as potent barriers to their cross-species transmission. TRIM5 alpha orthologues from different primates have distinct retroviral restriction patterns, largely dictated by the sequence of their C-terminal PRYSPRY domain, which binds the capsid protein of incoming virions. Here, by combining genetic and functional analyses of human and squirrel monkey TRIM5 alpha, we demonstrate that the coiled-coil domain of this protein, thus far essentially known for mediating oligomerization, also conditions the spectrum of antiretroviral activity. Furthermore, we identify three coiled-coil residues responsible for this effect, one of which has been under positive selection during primate evolution, notably in New World monkeys. These results indicate that the PRYSPRY and coiled-coil domains cooperate to determine the specificity of TRIM5 alpha-mediated capture of retroviral capsids, shedding new light on this complex event.

Soft tissue sarcomas with complex genomic profiles.

Soft tissue sarcomas (STS) with complex genomic profiles (50% of all STS) are predominantly composed of spindle cell/pleomorphic sarcomas, including leiomyosarcoma, myxofibrosarcoma, pleomorphic liposarcoma, pleomorphic rhabdomyosarcoma, malignant peripheral nerve sheath tumor, angiosarcoma, extraskeletal osteosarcoma, and spindle cell/pleomorphic unclassified sarcoma (previously called spindle cell/pleomorphic malignant fibrous histiocytoma). These neoplasms show, characteristically, gains and losses of numerous chromosomes or chromosome regions, as well as amplifications. Many of them share recurrent aberrations (e.g., gain of 5p13-p15) that seem to play a significant role in tumor progression and/or metastatic dissemination. In this paper, we review the cytogenetic, molecular genetic, and clinicopathologic characteristics of the most common STS displaying complex genomic profiles. Features of diagnostic or prognostic relevance will be discussed when needed.

Evaluating sampling strategies and logistic regression methods for modelling complex land cover changes

The role of land cover change as a significant component of global change has become increasingly recognized in recent decades. Large databases measuring land cover change, and the data which can potentially be used to explain the observed changes, are also becoming more commonly available. When developing statistical models to investigate observed changes, it is important to be aware that the chosen sampling strategy and modelling techniques can influence results. We present a comparison of three sampling strategies and two forms of grouped logistic regression models (multinomial and ordinal) in the investigation of patterns of successional change after agricultural land abandonment in Switzerland. Results indicated that both ordinal and nominal transitional change occurs in the landscape and that the use of different sampling regimes and modelling techniques as investigative tools yield different results. Synthesis and applications. Our multimodel inference identified successfully a set of consistently selected indicators of land cover change, which can be used to predict further change, including annual average temperature, the number of already overgrown neighbouring areas of land and distance to historically destructive avalanche sites. This allows for more reliable decision making and planning with respect to landscape management. Although both model approaches gave similar results, ordinal regression yielded more parsimonious models that identified the important predictors of land cover change more efficiently. Thus, this approach is favourable where land cover change pattern can be interpreted as an ordinal process. Otherwise, multinomial logistic regression is a viable alternative.

Shallow-level migmatization of gabbros in a metamorphic contact aureole, Fuerteventura Basal Complex, Canary Islands

Migmatization of gabbroic rocks at 2-3 kbar has occurred in the metamorphic contact aureole of a mafic pluton in the Fuerteventura Basal Complex (Canary Island;). Migmatites are characterized by a dense network: of closely spaced millimetre-wide leucocratic veins with perfectly preserved igneous textures. They are all relatively enriched in Al, Na I: Sr Ba, Nb, Y and the rare earth elements compared with the unaffected country rock beyond the aureole. Migmatization under such low-pressure conditions war possible because of the unusual tectonic and magmatic contact in which ii occurred. Multiple basic intrusions associated with extrusive volcanic activity created high heat flow in a small area. Alkaline and metasomatized rocks present in the country rock of the intruding pluton were leached by high-temperature fluids during contact metamorphism. These enriched fluids then favoured partial melting of the host gabbroic rocks, and contaminated both the leucosomes and melanosomes. A transpressive tectonic setting at the time of intrusion created shearing along the contact between the intrusion and its host rock. This shearing enhanced circulation of the fluids and allowed segregation of the nea-formed melts from their restite by opening tension veins into which the melts migrated. Depending on the relative timing of melt segregation and recrystallization leucosomes range in composition from a 40-60% mixture of clinopyroxene (+/- amphibole) and plagioclase to almost pure feldspathic veins. Comparable occurrences of gabbros migmatized at low pressure are expected only at a snail scale in localized areas of high heat flow in the presence of fluids, such as in. mid-ocean ridges or ocean-islands.