A ontogenia da nadadeira sarcopterígea elucida a origem das mãos com dedos

quarta-feira, agosto 26, 2020

Sarcopterygian fin ontogeny elucidates the origin of hands with digits

Joost M. Woltering1,*, Iker Irisarri1,†, Rolf Ericsson2,‡, Jean M. P. Joss2, Paolo Sordino3 and Axel Meyer1

Science Advances 19 Aug 2020:

Vol. 6, no. 34, eabc3510


How the hand and digits originated from fish fins during the Devonian fin-to-limb transition remains unsolved. Controversy in this conundrum stems from the scarcity of ontogenetic data from extant lobe-finned fishes. We report the patterning of an autopod-like domain by hoxa13 during fin development of the Australian lungfish, the most closely related extant fish relative of tetrapods. Differences from tetrapod limbs include the absence of digit-specific expansion of hoxd13 and hand2 and distal limitation of alx4 and pax9, which potentially evolved through an enhanced response to shh signaling in limbs. These developmental patterns indicate that the digit program originated in postaxial fin radials and later expanded anteriorly inside of a preexisting autopod-like domain during the evolution of limbs. Our findings provide a genetic framework for the transition of fins into limbs that supports the significance of classical models proposing a bending of the tetrapod metapterygial axis.

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Introduction to Phylogenetic Networks - David A. Morrison

quinta-feira, agosto 20, 2020


Recent advances in rooted phylogenetic networks: the long road to ...


Darwin, o problema da forma biológica permanece sem solução, mano!

segunda-feira, agosto 17, 2020

 On the problem of biological form

Marta Linde-Medina 

Theory in Biosciences volume 139, pages299–308(2020)

Ver a imagem de origem



Embryonic development, which inspired the first theories of biological form, was eventually excluded from the conceptual framework of the Modern Synthesis as irrelevant. A major question during the last decades has centred on understanding whether new advances in developmental biology are compatible with the standard view or whether they compel a new theory. Here, I argue that the answer to this question depends on which concept of morphogenesis is held. Morphogenesis can be conceived as (1) a chemically driven or (2) a mechanically driven process. According to the first option, genetic regulatory networks drive morphogenesis. According to the second, morphogenesis results from an invariant tendency of embryonic tissues to restore changes in mechanical stress. While chemically driven morphogenesis allows an extension of the standard view, mechanically driven morphogenesis would deeply transform it. Which of these hypotheses has wider explanatory power is unknown. At present, the problem of biological form remains unsolved.

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Darwin, modelar a biologia evolutiva na física não funciona, mano!

Historicity at the heart of biology

Maël Montévil 

Theory in Biosciences (2020)


Most mathematical modeling in biology relies either implicitly or explicitly on the epistemology of physics. The underlying conception is that the historicity of biological objects would not matter to understand a situation here and now, or, at least, historicity would not impact the method of modeling. We analyze that it is not the case with concrete examples. Historicity forces a conceptual reconfiguration where equations no longer play a central role. We argue that all observations depend on objects defined by their historical origin instead of their relations as in physics. Therefore, we propose that biological variations and historicity come first, and regularities are constraints with limited validity in biology. Their proper theoretical and empirical use requires specific rationales.

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Artigo de 2017 esperava sanar as fissuras/encobrir as rachaduras na biologia evolutiva

Evolutionary Biology volume 45, pages 127–139 (2018)

Hierarchy Theory of Evolution and the Extended Evolutionary Synthesis: Some Epistemic Bridges, Some Conceptual Rifts

Alejandro Fábregas-Tejeda & Francisco Vergara-Silva

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Contemporary evolutionary biology comprises a plural landscape of multiple co-existent conceptual frameworks and strenuous voices that disagree on the nature and scope of evolutionary theory. Since the mid-eighties, some of these conceptual frameworks have denounced the ontologies of the Modern Synthesis and of the updated Standard Theory of Evolution as unfinished or even flawed. In this paper, we analyze and compare two of those conceptual frameworks, namely Niles Eldredge’s Hierarchy Theory of Evolution (with its extended ontology of evolutionary entities) and the Extended Evolutionary Synthesis (with its proposal of an extended ontology of evolutionary processes), in an attempt to map some epistemic bridges (e.g. compatible views of causation; niche construction) and some conceptual rifts (e.g. extra-genetic inheritance; different perspectives on macroevolution; contrasting standpoints held in the “externalism–internalism” debate) that exist between them. This paper seeks to encourage theoretical, philosophical and historiographical discussions about pluralism or the possible unification of contemporary evolutionary biology.

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Microscopia revisitada

Revealing architectural order with quantitative label-free imaging and deep learning

Syuan-Ming Guo, Li-Hao Yeh, Jenny Folkesson, Ivan E Ivanov, Anitha P Krishnan, Matthew G Keefe, Ezzat Hashemi, David Shin, Bryant B Chhun, Nathan H Cho, Manuel D Leonetti, May H Han, Tomasz J Nowakowski, Shalin B Mehta 

Chan Zuckerberg Biohub, United States; Department of Anatomy, University of California, San Francisco, United States; Department of Neurology, Stanford University, United States


We report quantitative label-free imaging with phase and polarization (QLIPP) for simultaneous measurement of density, anisotropy, and orientation of structures in unlabeled live cells and tissue slices. We combine QLIPP with deep neural networks to predict fluorescence images of diverse cell and tissue structures. QLIPP images reveal anatomical regions and axon tract orientation in prenatal human brain tissue sections that are not visible using brightfield imaging. We report a variant of U-Net architecture, multi-channel 2.5D U-Net, for computationally efficient prediction of fluorescence images in three dimensions and over large fields of view. Further, we develop data normalization methods for accurate prediction of myelin distribution over large brain regions. We show that experimental defects in labeling the human tissue can be rescued with quantitative label-free imaging and neural network model. We anticipate that the proposed method will enable new studies of architectural order at spatial scales ranging from organelles to tissue.

eLife digest

Microscopy is central to biological research and has enabled scientist to study the structure and dynamics of cells and their components within. Often, fluorescent dyes or trackers are used that can be detected under the microscope. However, this procedure can sometimes interfere with the biological processes being studied.

Now, Guo, Yeh, Folkesson et al. have developed a new approach to examine structures within tissues and cells without the need for a fluorescent label. The technique, called QLIPP, uses the phase and polarization of the light passing through the sample to get information about its makeup.

A computational model was used to decode the characteristics of the light and to provide information about the density and orientation of molecules in live cells and brain tissue samples of mice and human. This way, Guo et al. were able to reveal details that conventional microscopy would have missed. Then, a type of machine learning, known as ‘deep learning’, was used to translate the density and orientation images into fluorescence images, which enabled the researchers to predict specific structures in human brain tissue sections.

QLIPP can be added as a module to a microscope and its software is available open source. Guo et al. hope that this approach can be used across many fields of biology, for example, to map the connectivity of nerve cells in the human brain or to identify how cells respond to infection. However, further work in automating other aspects, such as sample preparation and analysis, will be needed to realize the full benefits.


Mais uma hipótese sobre a origem da vida: surgimento de atividade catalítica em um autorreplicador

terça-feira, agosto 04, 2020

Chance emergence of catalytic activity and promiscuity in a self-replicator

Jim Ottelé, Andreas S. Hussain, Clemens Mayer & Sijbren Otto

Nature Catalysis volume 3, pages547–553(2020)


How life can emerge from inanimate matter is one of the grand questions in science. Self-replicating molecules are necessary for the transition from chemistry to biology, but they need to acquire additional functions for life to emerge. Catalysis is one of the most essential of such functionalities, but mechanisms through which self-replicators can acquire catalytic and, in extension, metabolic properties have remained elusive. Here we show how catalytic activity and promiscuity in a self-replicator emerges through co-option: features that are selected to benefit replication inadvertently result in an arrangement of chemical functionalities that is conducive to catalysis. Specifically, we report self-assembly driven self-replicators that promote both a model retro-aldol reaction and the cleavage of fluorenylmethoxycarbonyl groups, with the latter transformation exerting a positive feedback on replication (protometabolism). Such chance invention of new function at the molecular level marks a pivotal step toward the de novo synthesis of life.