Modularity, criticality, and evolvability of a developmental gene regulatory network

The existence of discrete phenotypic traits suggests that the complex regulatory processes which produce them are functionally modular. These processes are usually represented by networks. Only modular networks can be partitioned into intelligible subcircuits able to evolve relatively independently. Traditionally, functional modularity is approximated by detection of modularity in network structure. However, the correlation between structure and function is loose. Many regulatory networks exhibit modular behaviour without structural modularity. Here we partition an experimentally tractable regulatory network—the gap gene system of dipteran insects—using an alternative approach. We show that this system, although not structurally modular, is composed of dynamical modules driving different aspects of whole-network behaviour. All these subcircuits share the same regulatory structure, but differ in components and sensitivity to regulatory interactions. Some subcircuits are in a state of criticality, while others are not, which explains the observed differential evolvability of the various expression features in the system

Atmospheric dust captation by ornamental species

Se clasificaron 90 especies de árboles y arbustos de uso frecuente en Mendoza (Argentina) en base a su capacidad de filtrado del particulado atmosférico en suspensión. Se utilizó colectores de polvo atmosférico impregnados en vaselina líquida como superficie adherente. Se analizó por turbi-dimetría en un Hach 2100 P, con lectura en unidades nefelométricas de turbidez (NTU). Dichos colectores de polvo se colocaron en el interior y el exterior de la copa de cada ejemplar, con un mínimo de 15 repeticiones para cada posición. Por diferencia de promedios de lectura entre el exterior y el interior de la copa se obtuvo, en cada caso, un valor característico. Para lograr valores comparables entre ejemplares, con variaciones producidas por el follaje, debe referirse la mencionada diferencia del ancho de copa atravesado por el aire que transporta el contaminante y una lectura unitaria, mediante la relación: ILi =[(Loi -Lci) / (Efi * Loi)] * 100 m-1 donde: • ILi = índice de lectura interferométrica de la especie "i" • Loi= lectura interferométrica exterior (promedio de NTU externos) • Lci= lectura interferométrica interior de la copa (promedio de NTU internos) • Efi = espesor - expresado en m- de la copa en línea recta horizontal. El ILI, por caracterizar cada especie según su capacidad de captación de polvo atmosférico, permite el mejor uso de las mismas en proyectos de espacios verdes para protección ambiental.Based in the capacity to filtrate the atmospheric particulate it was established a classification of 90 vegetable species: shrubs and trees, frequently used in Mendoza (Argentina). The method used atmospheric dust collectors, impregnated in liquid vaseline as adherent surface, which are analyzed by a turbidimeter Hach 2100 P, with digital lectures in nefelometric turbidimeter units (NTU). In the samples these collectors were situated inside and outside of the canopy, at least in a number of 15 repetitions for each position. By difference of averages lectures among outside and inside, is reached the characteristicvalue for the specimen. This difference must be related to the canopy´s width crossed by the air current and to the unitary lecture, to obtain comparable values among different specimens, with variations produced by the characteristics of foliage. Itwas stablishedthe following relation: ILi = [ (Loi -Lci)/ (Efi * Loi )] * 100[m-1 where • ILi=interferometric lecture index of the specie "i" • Loi = outside interferometric lecture (average of externals NTU) • Lci= inside interferometric lecture (average of internals NTU) • Efi= width -expressed in m-of canopy crossed by air current, in horizontal straight line. The ILI index allow to characterize the vegetable species in order to their atmospheric dust captation capacity easing their utilization in green spaces projects and in environmental protection.Fil: Codina, Ramón A.. Universidad Nacional de Cuyo. Facultad de Ciencias AgrariasFil: Fioretti, Sonia B.. Universidad Nacional de Cuyo. Facultad de Ciencias AgrariasFil: Pérez, Paola V.. Universidad Nacional de Cuyo. Facultad de Ciencias AgrariasFil: Ureta, Norberto M.. Universidad Nacional de Cuyo. Facultad de Ciencias AgrariasFil: Llera, Joaquín. Universidad Nacional de Cuyo. Facultad de Ciencias AgrariasFil: Verd, Patricia. Universidad Nacional de Cuyo. Facultad de Ciencias AgrariasFil: Carrieri, Sergio A.. Universidad Nacional de Cuyo. Facultad de Ciencias AgrariasFil: Manzano, Enrique R.. Universidad Nacional de Cuyo. Facultad de Ciencias Agraria

The neural basis of perceived intensity in natural and artificial touch

Electrical stimulation of sensory nerves is a powerful tool for studying neural coding because it can activate neural populations in ways that natural stimulation cannot. Electrical stimulation of the nerve has also been used to restore sensation to patients who have suffered the loss of a limb. We have used long-term implanted electrical interfaces to elucidate the neural basis of perceived intensity in the sense of touch. To this end, we assessed the sensory correlates of neural firing rate and neuronal population recruitment independently by varying two parameters of nerve stimulation: pulse frequency and pulse width. Specifically, two amputees, chronically implanted with peripheral nerve electrodes, performed each of three psychophysical tasks-intensity discrimination, magnitude scaling, and intensity matching-in response to electrical stimulation of their somatosensory nerves. We found that stimulation pulse width and pulse frequency had systematic, cooperative effects on perceived tactile intensity and that the artificial tactile sensations could be reliably matched to skin indentations on the intact limb. We identified a quantity we termed the activation charge rate (ACR), derived from stimulation parameters, that predicted the magnitude of artificial tactile percepts across all testing conditions. On the basis of principles of nerve fiber recruitment, the ACR represents the total population spike count in the activated neural population. Our findings support the hypothesis that population spike count drives the magnitude of tactile percepts and indicate that sensory magnitude can be manipulated systematically by varying a single stimulation quantity

Aristotelian Essentialism: Essence in the Age of Evolution

The advent of contemporary evolutionary theory ushered in the eventual decline of Aristotelian Essentialism (Æ) – for it is widely assumed that essence does not, and cannot have any proper place in the age of evolution. This paper argues that this assumption is a mistake: if Æ can be suitably evolved, it need not face extinction. In it, I claim that if that theory’s fundamental ontology consists of dispositional properties, and if its characteristic metaphysical machinery is interpreted within the framework of contemporary evolutionary developmental biology, an evolved essentialism is available. The reformulated theory of Æ offered in this paper not only fails to fall prey to the typical collection of criticisms, but is also independently both theoretically and empirically plausible. The paper contends that, properly understood, essence belongs in the age of evolution

The ontology of organisms: Mechanistic modules or patterned processes?

Though the realm of biology has long been under the philosophical rule of the mechanistic magisterium, recent years have seen a surprisingly steady rise in the usurping prowess of process ontology. According to its proponents, theoretical advances in the contemporary science of evo-devo have afforded that ontology a particularly powerful claim to the throne: in that increasingly empirically confirmed discipline, emergently autonomous, higher-order entities are the reigning explanantia. If we are to accept the election of evo-devo as our best conceptualisation of the biological realm with metaphysical rigour, must we depose our mechanistic ontology for failing to properly “carve at the joints” of organisms? In this paper, I challenge the legitimacy of that claim: not only can the theoretical benefits offered by a process ontology be had without it, they cannot be sufficiently grounded without the metaphysical underpinning of the very mechanisms which processes purport to replace. The biological realm, I argue, remains one best understood as under the governance of mechanistic principles

Gene switching rate determines response to extrinsic perturbations in the self-activation transcriptional network motif

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A deep learning approach for staging embryonic tissue isolates with small data

Machine learning approaches are becoming increasingly widespread and are now present in most areas of research. Their recent surge can be explained in part due to our ability to generate and store enormous amounts of data with which to train these models. The requirement for large training sets is also responsible for limiting further potential applications of machine learning, particularly in fields where data tend to be scarce such as developmental biology. However, recent research seems to indicate that machine learning and Big Data can sometimes be decoupled to train models with modest amounts of data. In this work we set out to train a CNN-based classifier to stage zebrafish tail buds at four different stages of development using small information-rich data sets. Our results show that two and three dimensional convolutional neural networks can be trained to stage developing zebrafish tail buds based on both morphological and gene expression confocal microscopy images, achieving in each case up to 100% test accuracy scores. Importantly, we show that high accuracy can be achieved with data set sizes of under 100 images, much smaller than the typical training set size for a convolutional neural net. Furthermore, our classifier shows that it is possible to stage isolated embryonic structures without the need to refer to classic developmental landmarks in the whole embryo, which will be particularly useful to stage 3D culture in vitro systems such as organoids. We hope that this work will provide a proof of principle that will help dispel the myth that large data set sizes are always required to train CNNs, and encourage researchers in fields where data are scarce to also apply ML approaches