Nova teoria de geometria embrionária se propõe explicar a evolução dos vertebrados

quarta-feira, agosto 31, 2016

Progress in Biophysics and Molecular Biology

Volume 121, Issue 3, September 2016, Pages 212–244

Origin of the vertebrate body plan via mechanically biased conservation of regular geometrical patterns in the structure of the blastula

David B. Edelman a, , , Mark McMenamin b, , Peter Sheesley c, , Stuart Pivar d, 

a Department of Psychological Sciences, University of San Diego, Serra Hall 158, 5998 Alcalá Park, San Diego, CA 92110, USA

b 303 Clapp Laboratory, Mount Holyoke College, 50 College Street, South Hadley, MA 01075, USA

c Evergreen State College, 2700 Evergreen Pkwy NW, Olympia, WA 98505, USA

d Chief Scientific Officer and Chairman, Chem-Tainer Industries, Inc., 361Neptune Avenue, West Babylon, NY 11704, USA

Received 27 May 2016, Revised 24 June 2016, Accepted 28 June 2016, Available online 5 July 2016

Under a Creative Commons license

Source/Fonte: gekaskr - Fotolia


We present a plausible account of the origin of the archetypal vertebrate bauplan. We offer a theoretical reconstruction of the geometrically regular structure of the blastula resulting from the sequential subdivision of the egg, followed by mechanical deformations of the blastula in subsequent stages of gastrulation. We suggest that the formation of the vertebrate bauplan during development, as well as fixation of its variants over the course of evolution, have been constrained and guided by global mechanical biases. Arguably, the role of such biases in directing morphology—though all but neglected in previous accounts of both development and macroevolution—is critical to any substantive explanation for the origin of the archetypal vertebrate bauplan. We surmise that the blastula inherently preserves the underlying geometry of the cuboidal array of eight cells produced by the first three cleavages that ultimately define the medial-lateral, dorsal-ventral, and anterior-posterior axes of the future body plan. Through graphical depictions, we demonstrate the formation of principal structures of the vertebrate body via mechanical deformation of predictable geometrical patterns during gastrulation. The descriptive rigor of our model is supported through comparisons with previous characterizations of the embryonic and adult vertebrate bauplane. Though speculative, the model addresses the poignant absence in the literature of any plausible account of the origin of vertebrate morphology. A robust solution to the problem of morphogenesis—currently an elusive goal—will only emerge from consideration of both top-down (e.g., the mechanical constraints and geometric properties considered here) and bottom-up (e.g., molecular and mechano-chemical) influences.


Blastula; Gastrula; Evolution; Geometry; Morphogenesis; Vertebrate bauplan

Rosalind Franklin: a heroína esquecida do DNA - Cláudio L. Guerra

A visão dinâmica de polarização dos camarões louva-a-Deus

Dynamic polarization vision in mantis shrimps

Ilse M. Daly, Martin J. How, Julian C. Partridge, Shelby E. Temple, N. Justin Marshall, Thomas W. Cronin & Nicholas W. Roberts

Nature Communications 7, Article number: 12140 (2016)

Received: 04 January 2016 Accepted: 06 June 2016 Published online: 12 July 2016

(a) Side view of a Gonodactylus smithii. (b) Rotational degrees of freedom of stomatopod eyes relative to the external environment, as demonstrated in Odontodactylus cultrifer. Yellow arrows=pitch (up–down); green arrows=yaw (side-to-side); red arrows=torsional (roll) rotations. The midband is visible as a distinct stripe of ommatidial facets dividing the eye into dorsal and ventral hemispheres. (c,d) Series of video still frames demonstrating the torsional rotation range in G. smithii (c) and Odontodactylus scyllarus (d). (c) left eye - 45°, 85°, 0°; right eye - 30°, 20°, 90°; and (d) left eye - 90°, 80°, 0°; right eye - 90°, 0°, 90°.


Gaze stabilization is an almost ubiquitous animal behaviour, one that is required to see the world clearly and without blur. Stomatopods, however, only fix their eyes on scenes or objects of interest occasionally. Almost uniquely among animals they explore their visual environment with a series pitch, yaw and torsional (roll) rotations of their eyes, where each eye may also move largely independently of the other. In this work, we demonstrate that the torsional rotations are used to actively enhance their ability to see the polarization of light. Both Gonodactylus smithii and Odontodactylus scyllarus rotate their eyes to align particular photoreceptors relative to the angle of polarization of a linearly polarized visual stimulus, thereby maximizing the polarization contrast between an object of interest and its background. This is the first documented example of any animal displaying dynamic polarization vision, in which the polarization information is actively maximized through rotational eye movements.


We thank Michelle Cole and Holly Campbell for their help with animal care and the staff at the Lizard Island Research Station. Roy Caldwell and Michael Bok for their wonderful photographs. The study was funded by the Air Force Office of Scientific Research (grant # FA8655-12-2112), the Engineering and Physical Sciences Research Council (grant # EP/M000885/1). Biotechnology and Biological Sciences Research Council (grant # BB/J014400/1), the European Commission (grant # 656070/PLACAV) and the Royal Society (grant # UF140558).

Author information


School of Biological Sciences, University of Bristol, Tyndall Avenue, Bristol BS8 1TQ, UK

Ilse M. Daly, Martin J. How, Shelby E. Temple & Nicholas W. Roberts

School of Animal Biology and the Oceans Institute, University of Western Australia, 35 Stirling Highway (M317), Crawley, Western Australia 6009, Australia

Julian C. Partridge

Queensland Brain Institute, The University of Queensland, St Lucia, Queensland 4072, Australia

N. Justin Marshall

Department of Biological Sciences, University of Maryland Baltimore County, 1000 Hilltop Circle, Baltimore, Maryland 21250, USA

Thomas W. Cronin


I.M.D. performed all the experiments. S.E.T. helped with the construction of the LCD screen. I.M.D, M.J.H and N.W.R designed the experiments and analysed the data. All authors helped write and edit the manuscript.

Competing interests

The authors declare no competing financial interests.

Corresponding author

Correspondence to Nicholas W. Roberts.

Creative CommonsThis work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit

Nature Communications ISSN 2041-1723 (online)

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A genômica das formigas deu 'xeque-mate' na hipótese da Rainha Vermelha

sexta-feira, agosto 26, 2016

Comparative genomics reveals convergent rates of evolution in ant–plant mutualisms

Benjamin E. R. Rubin & Corrie S. Moreau

Nature Communications 7, Article number: 12679 (2016)

Comparative genomics Evolutionary ecology Evolutionary genetics Molecular evolution

Received: 27 November 2015 Accepted: 22 July 2016 Published online: 25 August 2016


Symbiosis—the close and often long-term interaction of species—is predicted to drive genome evolution in a variety of ways. For example, parasitic interactions have been shown to increase rates of molecular evolution, a trend generally attributed to the Red Queen Hypothesis. However, it is much less clear how mutualisms impact the genome, as both increased and reduced rates of change have been predicted. Here we sequence the genomes of seven species of ants, three that have convergently evolved obligate plant–ant mutualism and four closely related species of non-mutualists. Comparing these sequences, we investigate how genome evolution is shaped by mutualistic behaviour. We find that rates of molecular evolution are higher in the mutualists genome wide, a characteristic apparently not the result of demography. Our results suggest that the intimate relationships of obligate mutualists may lead to selective pressures similar to those seen in parasites, thereby increasing rates of evolution.

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Ehud Keinan 'falou e disse': somos todos computadores biomoleculares!

"Todos os sistemas biológicos ... são computadores moleculares naturais. Cada um de nós é um computador biomolecular, isto é, uma máquina na qual todos os componentes são moléculas "falando" uma com a outra de modo lógico. O hardware e o software são moléculas biológicas complexas que se ativam para desempenhar algumas tarefas químicas predeterminadas. O input é uma molécula que passa por mudanças programadas específicas, seguindo uma série de regras específicas (software), e o output deste processo de computação química é outra molécula bem definida."

"All biological systems ... are natural molecular computers. Every one of us is a biomolecular computer, that is, a machine in which all components are molecules "talking" to one another in a logical manner. The hardware and software are complex biological molecules that activate one another to carry out some predetermined chemical tasks. The input is a molecule that undergoes specific, programmed changes, following a specific set of rules (software) and the output of this chemical computation process is another well defined molecule."

— Ehud Keinan, American Technion Society, May 2013



O Prof. Dr. Ehud Keinan não faz parte do Design Inteligente.

Um novo passo em recriar a primeira vida na Terra

A New Step in Re-Creating First Life on Earth

An RNA molecule that can make copies of a variety of RNAs adds new support to the RNA-world theory.

Olena Shmahalo/Quanta Magazine

August 25, 2016

One of the biggest mysteries in the origin of life is how the first biological molecules came into being. Today’s cells use complex assemblies of biological molecules to manufacture DNA, RNA and proteins. How did life work before those molecules existed?

The predominant theory, known as the “RNA world,” proposes that RNA was the first biological molecule. RNA possesses the two essential properties needed for life: It can encode information (like DNA), and it can catalyze biological reactions (like proteins). Perhaps life began with an RNA or RNA-like molecule capable of copying itself, transmitting its genetic information to the next generation.

But the RNA-world theory has a gaping hole. Scientists have been unable to create such a molecule in the lab. Since the 1990s they’ve been able to make RNA enzymes, or ribozymes, that can make complementary copies of an RNA template — an RNA sequence like AACU could be copied into the complementary UUGA, for example. But actually replicating RNA requires two steps, moving from AACU to UUGA and then back again to AACU. Another difficulty is that existing RNA enzymes can’t make long or complex molecules.

Now, for the first time, scientists have produced an RNA enzyme that can make a wide range of RNA sequences. It can also replicate most RNA molecules up to 24 letters long. “Our ribozyme is the first one to replicate RNA in a base-by-base manner, the same way it is done in nature,” said David Horning, a researcher at the Scripps Research Institute in La Jolla, California, who did the work with Gerald Joyce, also at Scripps. The study was published this month in the Proceedings of the National Academy of Sciences.

The researchers started with an existing ribozyme and added random changes to the sequence to create a trillion slightly different versions. The researchers then subjected the pool of ribozymes to a challenge. They selected only those that were capable of making two different complex RNA molecules. They then repeated the process two dozen times — subjecting the molecules that passed each level of challenges to increasingly stringent challenges — to find the candidates that could make the 30-letter RNAs the fastest. This technique, known as experimental evolution, or test-tube evolution, is an artificial version of natural selection. Researchers introduce a few new mutations after each round of the experiment.

The molecule that made the new RNAs most efficiently, known as polymerase ribozyme 24-3, worked surprisingly well. It could synthesize a variety of RNA sequences with complex structures, not just the two from the initial tests. And it was much more efficient than the original ribozyme in making simple RNA molecules.



Erros na nomenclatura de genes ocorrem amplamente na literatura científica: Excel da Microsoft

quinta-feira, agosto 25, 2016

Gene name errors are widespread in the scientific literature

Mark Ziemann, Yotam Eren and Assam El-Osta Email author

Genome Biology201617:177

DOI: 10.1186/s13059-016-1044-7 © The Author(s). 2016

Published: 23 August 2016


The spreadsheet software Microsoft Excel, when used with default settings, is known to convert gene names to dates and floating-point numbers. A programmatic scan of leading genomics journals reveals that approximately one-fifth of papers with supplementary Excel gene lists contain erroneous gene name conversions.


Microsoft Excel Gene symbol Supplementary data


GEO: Gene Expression Omnibus

JIF: journal impact factor



We thank A. Kaspi and H. Rafehi for discussions on this paper, and R. Lazarus for informatics support.


AEO is supported by the National Health and Medical Research Council (NHMRC GNT0526681, GNT1048377); Juvenile Diabetes Research Foundation (JDRF 5-2008-298, 27-2012-451); Diabetes Australia Research Trust (DART); Victorian Government’s Operational Infrastructure Support program (in part).

Availability of data and materials

Bash scripts, URLs and output data supporting the conclusions of this article are available in the SourceForge repository

Authors’ contributions

MZ, YE and AEO designed and conducted analyses and co-wrote the manuscript. All authors read and approved the final manuscript.

Competing interests

The authors declare that they have no competing interests.

Ethics approval and consent to participate

No ethical approval was required.

Open Access

This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (, which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( applies to the data made available in this article, unless otherwise stated.

Additional file

Additional file 1: Table S1. List of supplementary files containing Excel gene name errors from journals and Gene Expression Omnibus (GEO). (XLSX 81 kb)

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Pesquisadores registram imagens de raízes no solo

quarta-feira, agosto 24, 2016

© Author(s) 2016. This work is distributed under the Creative Commons Attribution 3.0 License.

Multi-frequency electrical impedance tomography as a non-invasive tool to characterize and monitor crop root systems

Maximilian Weigand and Andreas Kemna

Department of Geophysics, University of Bonn, Meckenheimer Allee 176, 53115 Bonn, Germany

Received: 23 Apr 2016 – Accepted: 11 Jul 2016 – Published: 23 Aug 2016


A better understanding of root-soil interactions and associated processes is essential in achieving progress in crop breeding and management, prompting the need for high-resolution and non-destructive characterization methods. To date such methods are still lacking, or restricted by technical constraints, in particular for characterizing and monitoring root growth and function in the field. A promising technique in this respect is electrical impedance tomography (EIT), which utilizes low-frequency (< 1 kHz) electrical conduction and polarization properties in an imaging framework. It is well established that cells and cell clusters exhibit an electrical polarization response in alternating electric current fields due to electrical double layers which form at cell membranes. This double layer is directly related to the electrical surface properties of the membrane, which in turn are influenced by nutrient dynamics (fluxes and concentrations on both sides of the membranes). Therefore it can be assumed that the electrical polarization properties of roots are inherently related to nutrient uptake and translocation processes in the roots. We here propose broadband (mHz to hundreds of Hz) multi-frequency EIT as a non-invasive methodological approach for the monitoring and physiological, i.e. functional, characterization of crop root systems. The approach combines the spatial resolution capability of an imaging method with the diagnostic potential of electrical impedance spectroscopy. The capability of multi-frequency EIT to characterize and monitor crop root systems was investigated in a laboratory rhizotron experiment, in which the root system of oilseed plants was monitored in a water-filled rhizotron under ongoing nutrient deprivation. We found a low-frequency polarization response of the root system, which enabled the successful delineation of the spatial extension of the root system. The magnitude of the overall polarization response decreased along with the physiological decay of the root system due to the nutrient deprivation. Spectral polarization parameters, as derived from a pixel-based Debye decomposition analysis of the multi-frequency imaging results, reveal systematic changes in the spatial and spectral electrical response of the root system. In particular, quantified mean relaxation times (of the order of 10 ms) indicate changes in the length scales on which the polarization processes took place in the root system, as a response to prolonged nutrient deficiency. Our results demonstrate that broadband EIT is a capable non-invasive method to image root system extension as well as to monitor changes associated with root physiological processes. Given its applicability at both laboratory and field scales, our results suggest an enormous potential of the method for the structural and functional imaging of root system for various applications. This particularly holds for the field scale, where corresponding methods are highly desired but to date lacking.

Citation: Weigand, M. and Kemna, A.: Multi-frequency electrical impedance tomography as a non-invasive tool to characterize and monitor crop root systems, Biogeosciences Discuss., doi:10.5194/bg-2016-154, in review, 2016.

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Compreendendo os padrões da natureza através dos plasmas

Three-dimensional patterns in dielectric barrier discharge with “H” shaped gas gap

Xing Gao 1, Lifang Dong 1,a), Hao Wang 1, Hao Zhang 1, Ying Liu 1, Weibo Liu 1, Weili Fan 1 and Yuyang Pan 1


1 College of Physics Science and Technology, Hebei University, Baoding 071002, China

a) E-mail:

Phys. Plasmas 23, 083526 (2016);


Three-dimensional (3D) patterns are obtained for the first time in dielectric barrier discharge by a special designed device with “H” shaped gas gap which consists of a single gas layer gap and two double gas layer gaps. Three dimensional spatiotemporal characteristics of discharge are investigated by photomultiplier and intensified charge-coupled device camera. Results show that the discharge first generates in the single gas layer gap and the coupled filaments in the double gas layer gap present the simultaneity characteristics. The formation of 3D patterns is determined by the distribution of the effective field of the applied field and the wall charge field.

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Cérebro humano mais complexo do que uma galáxia!!!

terça-feira, agosto 23, 2016

Human high intelligence is involved in spectral redshift of biophotonic activities in the brain

Zhuo Wang a,b, Niting Wang a,b, Zehua Li a,b, Fangyan Xiao a,c, and Jiapei Dai a,b,c,1

Author Affiliations

a Wuhan Institute for Neuroscience and Neuroengineering, South-Central University for Nationalities, Wuhan 430074, China;

b Department of Neurobiology, The College of Life Sciences, South-Central University for Nationalities, Wuhan 430074, China;

c Chinese Brain Bank Center, Wuhan 430074, China

Edited by Michael A. Persinger, Laurentian University, Canada, and accepted by Editorial Board Member Marlene Behrmann May 20, 2016 (received for review March 24, 2016)

Source/Fonte: Daily Galaxy 


It is still unclear why human beings hold higher intelligence than other animals on Earth and which brain properties might explain the differences. The recent studies have demonstrated that biophotons may play a key role in neural information processing and encoding and that biophotons may be involved in quantum brain mechanism; however, the importance of biophotons in relation to animal intelligence, including that of human beings, is not clear. Here, we have provided experimental evidence that glutamate-induced biophotonic activities and transmission in brain slices present a spectral redshift feature from animals (bullfrog, mouse, chicken, pig, and monkey) to humans, which may be a key biophysical basis for explaining why human beings hold higher intelligence than that of other animals.


Human beings hold higher intelligence than other animals on Earth; however, it is still unclear which brain properties might explain the underlying mechanisms. The brain is a major energy-consuming organ compared with other organs. Neural signal communications and information processing in neural circuits play an important role in the realization of various neural functions, whereas improvement in cognitive function is driven by the need for more effective communication that requires less energy. Combining the ultraweak biophoton imaging system (UBIS) with the biophoton spectral analysis device (BSAD), we found that glutamate-induced biophotonic activities and transmission in the brain, which has recently been demonstrated as a novel neural signal communication mechanism, present a spectral redshift from animals (in order of bullfrog, mouse, chicken, pig, and monkey) to humans, even up to a near-infrared wavelength (∼865 nm) in the human brain. This brain property may be a key biophysical basis for explaining high intelligence in humans because biophoton spectral redshift could be a more economical and effective measure of biophotonic signal communications and information processing in the human brain.

intelligence ultraweak photon emissions biophoton imaging glutamate brain slices


1 To whom correspondence should be addressed. Email:

Author contributions: J.D. designed research; Z.W., N.W., F.X., and J.D. performed research; Z.W. and J.D. analyzed data; Z.L. contributed new reagents/analytic tools; and J.D. wrote the paper.

The authors declare no conflict of interest.

This article is a PNAS Direct Submission. M.A.P. is a Guest Editor invited by the Editorial Board.

This article contains supporting information online at


Cartilha de astrobiologia v2.0

The Astrobiology Primer v2.0

To cite this article:

Domagal-Goldman Shawn D., Wright Katherine E., Adamala Katarzyna, Arina de la Rubia Leigh, Bond Jade, Dartnell Lewis R., Goldman Aaron D., Lynch Kennda, Naud Marie-Eve, Paulino-Lima Ivan G., Singer Kelsi, Walter-Antonio Marina, Abrevaya Ximena C., Anderson Rika, Arney Giada, Atri Dimitra, Azúa-Bustos Armando, Bowman Jeff S., Brazelton William J., Brennecka Gregory A., Carns Regina, Chopra Aditya, Colangelo-Lillis Jesse, Crockett Christopher J., DeMarines Julia, Frank Elizabeth A., Frantz Carie, de la Fuente Eduardo, Galante Douglas, Glass Jennifer, Gleeson Damhnait, Glein Christopher R., Goldblatt Colin, Horak Rachel, Horodyskyj Lev, Kaçar Betül, Kereszturi Akos, Knowles Emily, Mayeur Paul, McGlynn Shawn, Miguel Yamila, Montgomery Michelle, Neish Catherine, Noack Lena, Rugheimer Sarah, Stüeken Eva E., Tamez-Hidalgo Paulina, Walker Sara Imari, and Wong Teresa. 

Astrobiology. August 2016, 16(8): 561-653. doi: 10.1089/ast.2015.1460.

Published in Volume: 16 Issue 8: August 1, 2016

Author information

Co-Lead Editors Shawn D. Domagal-Goldman and Katherine E. Wright Chapter Editors Shawn D. Domagal-Goldman (Co-Lead Editor, Co-Editor Chapter 1, and Author)1,2,* Katherine E. Wright (Co-Lead Editor, Co-Editor Chapter 1, and Author)3,4,* Katarzyna Adamala (Co-Editor Chapter 3 and Author)5 Leigh Arina de la Rubia (Editor Chapter 9 and Author)6 Jade Bond (Co-Editor Chapter 3 and Author)7 Lewis R. Dartnell (Co-Editor Chapter 7 and Author)8 Aaron D. Goldman (Editor Chapter 2 and Author)9 Kennda Lynch (Co-Editor Chapter 5 and Author)10 Marie-Eve Naud (Co-Editor Chapter 7 and Author)11 Ivan G. Paulino-Lima (Editor Chapter 8 and Author)12,13 Kelsi Singer (Co-Editor Chapter 5, Editor Chapter 6, and Author)14 Marina Walter-Antonio (Editor Chapter 4 and Author)15 Authors Ximena C. Abrevaya,16 Rika Anderson,17 Giada Arney,18 Dimitra Atri,13 Armando Azúa-Bustos,13,19 Jeff S. Bowman,20 William J. Brazelton,21 Gregory A. Brennecka,22 Regina Carns,23 Aditya Chopra,24 Jesse Colangelo-Lillis,25 Christopher J. Crockett,26 Julia DeMarines,13 Elizabeth A. Frank,27 Carie Frantz,28 Eduardo de la Fuente,29 Douglas Galante,30 Jennifer Glass,31 Damhnait Gleeson,32 Christopher R. Glein,33 Colin Goldblatt,34 Rachel Horak,35 Lev Horodyskyj,36 Betül Kaçar,37 Akos Kereszturi,38 Emily Knowles,39 Paul Mayeur,40 Shawn McGlynn,41 Yamila Miguel,42 Michelle Montgomery,43 Catherine Neish,44 Lena Noack,45 Sarah Rugheimer,46,47 Eva E. Stüeken,48,49 Paulina Tamez-Hidalgo,50 Sara Imari Walker,13,51 and Teresa Wong52

1 NASA Goddard Space Flight Center, Greenbelt, Maryland, USA.

2 Virtual Planetary Laboratory, Seattle, Washington, USA.

3 University of Colorado at Boulder, Colorado, USA.

4 Present address: UK Space Agency, UK.

5 Department of Genetics, Cell Biology and Development, University of Minnesota, Minneapolis, Minnesota, USA.

6 Tennessee State University, Nashville, Tennessee, USA.

7 Department of Physics, University of New South Wales, Sydney, Australia.

8 University of Westminster, London, UK.

9 Oberlin College, Oberlin, Ohio, USA.

10 Division of Biological Sciences, University of Montana, Missoula, Montana, USA.

11 Institute for research on exoplanets (iREx), Université de Montréal, Montréal, Canada.

12 Universities Space Research Association, Mountain View, California, USA.

13 Blue Marble Space Institute of Science, Seattle, Washington, USA.

14 Southwest Research Institute, Boulder, Colorado, USA.

15 Mayo Clinic, Rochester, Minnesota, USA.

16 Instituto de Astronomía y Física del Espacio (IAFE), UBA—CONICET, Ciudad Autónoma de Buenos Aires, Argentina.

17 Department of Biology, Carleton College, Northfield, Minnesota, USA.

18 University of Washington Astronomy Department and Astrobiology Program, Seattle, Washington, USA.

19 Centro de Investigación Biomédica, Universidad Autónoma de Chile, Santiago, Chile.

20 Lamont-Doherty Earth Observatory, Columbia University, Palisades, New York, USA.

21 Department of Biology, University of Utah, Salt Lake City, Utah, USA.

22 Institut für Planetologie, University of Münster, Münster, Germany.

23 Polar Science Center, Applied Physics Laboratory, University of Washington, Seattle, Washington, USA.

24 Planetary Science Institute, Research School of Earth Sciences, Research School of Astronomy and Astrophysics, The Australian National University, Canberra, Australia.

25 Earth and Planetary Science, McGill University, and the McGill Space Institute, Montréal, Canada.

26 Society for Science & the Public, Washington, DC, USA.

27 Carnegie Institute for Science, Washington, DC, USA.

28 Department of Geosciences, Weber State University, Ogden, Utah, USA.

29 IAM-Departamento de Fisica, CUCEI, Universidad de Guadalajara, Guadalajara, México.

30 Brazilian Synchrotron Light Laboratory, Campinas, Brazil.

31 School of Earth and Atmospheric Sciences, Georgia Institute of Technology, Atlanta, Georgia, USA.

32 Science Foundation Ireland, Dublin, Ireland.

33 Southwest Research Institute, San Antonio, Texas, USA.

34 School of Earth and Ocean Sciences, University of Victoria, Victoria, Canada.

35 American Society for Microbiology, Washington, DC, USA.

36 Arizona State University, Tempe, Arizona, USA.

37 Harvard University, Organismic and Evolutionary Biology, Cambridge, Massachusetts, USA.

38 Research Centre for Astronomy and Earth Sciences, Hungarian Academy of Sciences, Budapest, Hungary.

39 Johnson & Wales University, Denver, Colorado, USA.

40 Rensselaer Polytechnic Institute, Troy, New York, USA.

41 Earth Life Science Institute, Tokyo Institute of Technology, Tokyo, Japan.

42 Laboratoire Lagrange, UMR 7293, Université Nice Sophia Antipolis, CNRS, Observatoire de la Côte d'Azur, Nice, France.

43 University of Central Florida, Orlando, Florida, USA.

44 Department of Earth Sciences, The University of Western Ontario, London, Canada.

45 Royal Observatory of Belgium, Brussels, Belgium.

46 Department of Astronomy, Harvard University, Cambridge, Massachusetts, USA.

47 University of St. Andrews, St. Andrews, UK.

48 University of Washington, Seattle, Washington, USA.

49 University of California, Riverside, California, USA.

50 Novozymes A/S, Bagsvaerd, Denmark.

51 School of Earth and Space Exploration and Beyond Center for Fundamental Concepts in Science, Arizona State University, Tempe, Arizona, USA.

52 Department of Earth and Planetary Sciences, Washington University in St. Louis, St. Louis, Missouri, USA.

*These two authors contributed equally to the work.

Address correspondence to:

Shawn D. Domagal-Goldman

Planetary Environments Laboratory
NASA Goddard Space Flight Center
8800 Greenbelt Road
Mail Stop 699.0
Washington, MD 20771


Submitted 23 December 2015 Accepted 6 June 2016

Table of Contents

Chapter 1. Introduction—What Is Astrobiology?

Chapter 2. What Is Life?

Chapter 3. How Did Earth and Its Biosphere Originate?

Chapter 4. How Have Earth and Its Biosphere Evolved?

Chapter 5. What Does Life on Earth Tell Us about Habitability?

Chapter 6. What Is Known about Potentially Habitable Worlds beyond Earth?

Chapter 7. What Are the Signs of Life (Biosignatures) That We Could Use to Look for Life beyond Earth?

Chapter 8. What Relevance Does Astrobiology Have to the Future of Life on This Planet?

Chapter 9. Resources



Abbreviations List

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Uma perspectiva na busca de inteligência extraterrestre

Alien Mindscapes—A Perspective on the Search for Extraterrestrial Intelligence

To cite this article: Cabrol Nathalie A.. Astrobiology. July 2016, ahead of print. 

doi: 10.1089/ast.2016.1536Online Ahead of Print: July 6, 2016

Author information

Nathalie A. Cabrol
Carl Sagan Center, SETI Institute, Mountain View, California.

Address correspondence to:

Dr. Nathalie A. Cabrol
SETI Institute Carl Sagan Center
189 N Bernardo Ave. #200
Mountain View, CA 94043


Submitted 14 May 2016 Accepted 23 May 2016 


Advances in planetary and space sciences, astrobiology, and life and cognitive sciences, combined with developments in communication theory, bioneural computing, machine learning, and big data analysis, create new opportunities to explore the probabilistic nature of alien life. Brought together in a multidisciplinary approach, they have the potential to support an integrated and expanded Search for Extraterrestrial Intelligence (SETI1), a search that includes looking for life as we do not know it. This approach will augment the odds of detecting a signal by broadening our understanding of the evolutionary and systemic components in the search for extraterrestrial intelligence (ETI), provide more targets for radio and optical SETI, and identify new ways of decoding and coding messages using universal markers. Key Words: SETI—Astrobiology—Coevolution of Earth and life—Planetary habitability and biosignatures. Astrobiology 16, xxx–xxx.


I am particularly grateful to those who, through conversations, constructive criticism, suggestions, comments, and reviews at various stages of development have helped me articulate this perspective. Special thanks to Bill Diamond, David Darling, Margaret Race, Mark Showalter, and Jill Tarter for their inputs. Also thank you to Maggie Turnbull and Laurance Doyle for sharing thoughts over the past few months.

Author Disclosure Statement

The author declares no conflict of interest.

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Genes encontram seus 'parceiros' sem precisar de intermediários

segunda-feira, agosto 22, 2016

Evidence of protein-free homology recognition in magnetic bead force–extension experiments

D. J. (O’) Lee, C. Danilowicz, C. Rochester, A. A. Kornyshev, M. Prentiss

Published 20 July 2016.DOI: 10.1098/rspa.2016.0186


Earlier theoretical studies have proposed that the homology-dependent pairing of large tracts of dsDNA may be due to physical interactions between homologous regions. Such interactions could contribute to the sequence-dependent pairing of chromosome regions that may occur in the presence or the absence of double-strand breaks. Several experiments have indicated the recognition of homologous sequences in pure electrolytic solutions without proteins. Here, we report single-molecule force experiments with a designed 60 kb long dsDNA construct; one end attached to a solid surface and the other end to a magnetic bead. The 60 kb constructs contain two 10 kb long homologous tracts oriented head to head, so that their sequences match if the two tracts fold on each other. The distance between the bead and the surface is measured as a function of the force applied to the bead. At low forces, the construct molecules extend substantially less than normal, control dsDNA, indicating the existence of preferential interaction between the homologous regions. The force increase causes no abrupt but continuous unfolding of the paired homologous regions. Simple semi-phenomenological models of the unfolding mechanics are proposed, and their predictions are compared with the data.

Data accessibility

Data supporting this article are included in the electronic supplementary material. S1 contains additional supporting experimental data; S2 contains details on the background of Model 1; S3 discusses the approximations behind the equations for Lloop; S4 presents plots of the free energy for model 1 as well as a plot showing how Lloop varies with the parameter b in that model; S5 shows the fitted the values of the model parameters; S6 specifies exactly the DNA text that was added to the end of the λ DNA in the constructs.

Authors' contributions

D.J.(O’)L. had a major role in the writing of the paper and development of the theoretical models, as well as helping with the data analysis and curve fitting. C.D. designed and performed the experiments. C.R. helped with the data analysis and performed the curve fitting. A.A.K. participated in the development of the theory, discussion of experimental results and writing of the paper. M.P. designed the experiments, analysed data, as well as participated in writing the paper and the development of the theory.

Competing interests

The authors have no competing interests.


This work was supported by the National Institutes of Health to M.P. (grant no. R01 GM044794), the Human Frontier Science Program to A.A.K. (grant no. RG0049/2010-C102) and the grant of the Engineering and Physical Sciences Research Council, EP/H010106/1.


The authors acknowledge useful discussions with Nancy Kleckner and Tim Albrecht.

Received March 15, 2016. Accepted June 17, 2016. 

© 2016 The Authors.

Published by the Royal Society under the terms of the Creative Commons Attribution License, which permits unrestricted use, provided the original author and source are credited.


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