Projetando com DNA: Por que buscar design na natureza se isso é uma ilusão?

Automated design of 3D DNA origami with non-rasterized 2D curvature

Daniel Fu, Raghu Pradeep Narayanan, Abhay Prasad, Fei Zhang, Dewight Williams, John S. Schreck, Hao Yan, and John Reif

SCIENCE ADVANCES 23 Dec 2022 Vol 8, Issue 51 DOI: 10.1126/sciadv.ade4455

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Abstract

Improving the precision and function of encapsulating three-dimensional (3D) DNA nanostructures via curved geometries could have transformative impacts on areas such as molecular transport, drug delivery, and nanofabrication. However, the addition of non-rasterized curvature escalates design complexity without algorithmic regularity, and these challenges have limited the ad hoc development and usage of previously unknown shapes. In this work, we develop and automate the application of a set of previously unknown design principles that now includes a multilayer design for closed and curved DNA nanostructures to resolve past obstacles in shape selection, yield, mechanical rigidity, and accessibility. We design, analyze, and experimentally demonstrate a set of diverse 3D curved nanoarchitectures, showing planar asymmetry and examining partial multilayer designs. Our automated design tool implements a combined algorithmic and numerical approximation strategy for scaffold routing and crossover placement, which may enable wider applications of general DNA nanostructure design for nonregular or oblique shapes.

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Sobre a origem química da cognição biológica: mero acaso, fortuita necessidade ou design inteligente?

On the Chemical Origin of Biological Cognition

by Robert Pascal 1 and Addy Pross 2,*

1 Laboratoire de Physique des Interactions Ioniques et Moléculaires (PIIM), Aix-Marseille Université—CNRS, 13013 Marseille, France

2 Department of Chemistry, Ben-Gurion University of the Negev, Be’er-Sheva 8410501, Israel *

Author to whom correspondence should be addressed.

Life 2022, 12(12), 2016; https://doi.org/10.3390/life12122016

Received: 13 October 2022 / Revised: 21 November 2022 / Accepted: 1 December 2022 / Published: 3 December 2022

(This article belongs to the Special Issue The Origin and Early Evolution of Life: Prebiotic Chemistry Perspective)

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Abstract

One of life’s most striking characteristics is its mental dimension, one whose very existence within a material system has long been a deep scientific mystery. Given the current scientific view that life emerged from non-life, how was it possible for ‘dead’ matter to have taken on mental capabilities? In this Perspective we describe the existence of a recently discovered non-equilibrium state of matter, an energized dynamic kinetic state, and demonstrate how particular chemical systems once activated into that kinetic state could manifest rudimentary cognitive behavior. Thus, contrary to a common view that biology is not reducible to physics and chemistry, recent findings in both chemistry and biology suggest that life’s mental state is an outcome of its physical state, and therefore may be explicable in physical/chemical terms. Such understanding offers added insight into the physico-chemical process by which life was able to emerge from non-life and the perennial ‘what is life?’ question. Most remarkably, it appears that Darwin, through his deep understanding of the evolutionary process, already sensed the existence of a connection between life’s physical and mental states.

Keywords: origin of life; dynamic kinetic stability; thermodynamic stability; cognition; molecular replication; evolution; consciousness

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O que faltou ser considerado? A macroevolução como entendida classicamente...

Towards evolutionary predictions: Current promises and challenges

Meike T. Wortel, Deepa Agashe, Susan F. Bailey, Claudia Bank, Karen Bisschop, Thomas Blankers, Johannes Cairns, Enrico Sandro Colizzi, Davide Cusseddu, Michael M. Desai et al 

First published: 09 December 2022

https://doi.org/10.1111/eva.13513

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Abstract

Evolution has traditionally been a historical and descriptive science, and predicting future evolutionary processes has long been considered impossible. However, evolutionary predictions are increasingly being developed and used in medicine, agriculture, biotechnology and conservation biology. Evolutionary predictions may be used for different purposes, such as to prepare for the future, to try and change the course of evolution or to determine how well we understand evolutionary processes. Similarly, the exact aspect of the evolved population that we want to predict may also differ. For example, we could try to predict which genotype will dominate, the fitness of the population or the extinction probability of a population. In addition, there are many uses of evolutionary predictions that may not always be recognized as such. The main goal of this review is to increase awareness of methods and data in different research fields by showing the breadth of situations in which evolutionary predictions are made. We describe how diverse evolutionary predictions share a common structure described by the predictive scope, time scale and precision. Then, by using examples ranging from SARS-CoV2 and influenza to CRISPR-based gene drives and sustainable product formation in biotechnology, we discuss the methods for predicting evolution, the factors that affect predictability and how predictions can be used to prevent evolution in undesirable directions or to promote beneficial evolution (i.e. evolutionary control). We hope that this review will stimulate collaboration between fields by establishing a common language for evolutionary predictions.

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A biologia de sistemas é o estudo da engenharia de sistemas: igual ou superior ao da NASA?

Jan. 27, 2020

NASA Systems Engineering Handbook

Revision 2

In 1995, the NASA Systems Engineering Handbook (NASA/SP-6105) was initially published to bring the fundamental concepts and techniques of systems engineering to the National Aeronautics and Space Administration (NASA) personnel in a way that recognized the nature of NASA systems and the NASA environment. Since its initial writing and its revision in 2007 (Rev 1), systems engineering as a discipline at NASA has undergone rapid and continued evolution. This revision (Rev 2) of the Handbook maintains that original philosophy while updating the Agency’s systems engineering body of knowledge, providing guidance for insight into current best Agency practices, and maintaining the alignment of the Handbook with the Agency’s systems engineering policy.

The update of this Handbook continues the methodology of the previous revision: a top-down compatibility with higher-level Agency policy and a bottom-up infusion of guidance from the NASA practitioners in the field. This approach provides the opportunity to obtain best practices from across NASA and bridge the information to the established NASA systems engineering processes and to communicate principles of good practice as well as alternative approaches rather than specify a particular way to accomplish a task. The result embodied in this Handbook is a top-level implementation approach on the practice of systems engineering unique to NASA.

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Last Updated: Jan 27, 2020

Editor: Garrett Shea

Banco de Dados de Biologia – Uma Lista de Códigos Biológicos

 

National Human Genome Research Institute

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Analisando disparidade e taxas de evolução morfológica com métodos comparativos baseados em modelos filogenéticos

Analyzing Disparity and Rates of Morphological Evolution with Model-Based Phylogenetic Comparative Methods

Thomas F Hansen, Geir H Bolstad, Masahito Tsuboi

Systematic Biology, Volume 71, Issue 5, September 2022, Pages 1054–1072, https://doi.org/10.1093/sysbio/syab079

Published: 02 December 2021

Relative overall rates of morphological evolution in early tetrapodomorphs.

Nature Ecology & Evolution volume 5, pages1403–1414 (2021)

Abstract

Understanding variation in rates of evolution and morphological disparity is a goal of macroevolutionary research. In a phylogenetic comparative methods framework, we present three explicit models for linking the rate of evolution of a trait to the state of another evolving trait. This allows testing hypotheses about causal influences on rates of phenotypic evolution with phylogenetic comparative data. We develop a statistical framework for fitting the models with generalized least-squares regression and use this to discuss issues and limitations in the study of rates of evolution more generally. We show that the power to detect effects on rates of evolution is low in that even strong causal effects are unlikely to explain more than a few percent of observed variance in disparity. We illustrate the models and issues by testing if rates of beak-shape evolution in birds are influenced by brain size, as may be predicted from a Baldwin effect in which presumptively more behaviorally flexible large-brained species generate more novel selection on themselves leading to higher rates of evolution. From an analysis of morphometric data for 645 species, we find evidence that both macro- and microevolution of the beak are faster in birds with larger brains, but with the caveat that there are no consistent effects of relative brain size.

[Baldwin effect; beak shape; behavioral drive; bird; brain size; disparity; phylogenetic comparative method; rate of evolution.]

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