Science


A cargo-sorting DNA robot

Science

We developed a simple algorithm and three modular building blocks for a DNA robot that performs autonomous cargo sorting. The robot explores a two-dimensional testing ground on the surface of DNA origami, picks up multiple cargos of two types that are initially at unordered locations, and delivers each type to a specified destination until all cargo molecules are sorted into two distinct piles. On average, our robot performed approximately 300 steps while sorting the cargos. The number of steps is one to two magnitudes larger than the previously demonstrated DNA robots performing additional tasks while walking.


Memories of past morphologies

Science

When developing neurons round and divide during neuronal differentiation, daughter cells tend to take up the same morphology exhibited by their mother. These neurons differentiate from neural crest cells (NCCs) generated by bipolar progenitors. Bipolar NCCs lost their polarity and retracted their processes to round for division. The daughter neurons directly acquired bipolar morphology by emitting processes in the same location.


Wire together, fire apart

Science

It has been widely accepted that memories are formed and stored via strengthening of neural connections due to the correlated activities of neurons, where presumably one neuron is causing or at least contributing to the activity of another connecting neuron and hence becomes associated with it. This principle is known as the Hebbian learning rule (1): i.e., if interconnected neurons become active very close in time during a particular event, their connection strengthens and "a memory" of this event is formed (1). Thus, neural connection must show some sort of plasticity--i.e., an ability to be modified based on the mutual firing patterns of interconnected neurons--in order to form memories and associations. Indeed, it has been shown that brief (hundreds of milliseconds) stimulations of interconnected neurons significantly improve signal transmission between the two, a phenomenon known as long-term potentiation (LTP).


Hurricane Harvey provides lab for U.S. forecast experiments

Science

For years, U.S. forecasters have envied their colleagues at the European Centre for Medium-Range Weather Forecasts in Reading, U.K., whose hurricane prediction models remain the gold standard. But two innovations tested during Hurricane Harvey, one from NASA and another from the National Oceanic and Atmospheric Administration, could help level the playing field. The storm provided the first high-profile test for the next-generation weather model developed for the National Weather Service, which can zoom in on storms. And Harvey will help calibrate the Cyclone Global Navigation Satellite System, a NASA array of eight microsatellites that aim to detect the maximum wind speed of storms through their veil of moisture.


Emergent cellular self-organization and mechanosensation initiate follicle pattern in the avian skin

Science

This pattern arises when uniform fields of progenitor cells diversify their molecular fate while adopting higher-order structure. Using the nascent skin of the developing chicken embryo as a model system, we find that morphological and molecular symmetries are simultaneously broken by an emergent process of cellular self-organization. The key initiators of heterogeneity are dermal progenitors, which spontaneously aggregate through contractility-driven cellular pulling. Concurrently, this dermal cell aggregation triggers the mechanosensitive activation of β-catenin in adjacent epidermal cells, initiating the follicle gene expression program.


Conversion of object identity to object-general semantic value in the primate temporal cortex

Science

However, it remains elusive whether and how object percepts alone, or concomitantly a nonphysical attribute of the objects ("learned"), are decoded from perirhinal activities. By combining monkey psychophysics with optogenetic and electrical stimulations, we found a focal spot of memory neurons where both stimulations led monkeys to preferentially judge presented objects as "already seen." In an adjacent fringe area, where neurons did not exhibit selective responses to the learned objects, electrical stimulation induced the opposite behavioral bias toward "never seen before," whereas optogenetic stimulation still induced bias toward "already seen." These results suggest that mnemonic judgment of objects emerges via the decoding of their nonphysical attributes encoded by perirhinal neurons.


Two areas for familiar face recognition in the primate brain

Science

Familiarity alters face recognition: Familiar faces are recognized more accurately than unfamiliar ones and under difficult viewing conditions when unfamiliar face recognition fails. Using whole-brain functional magnetic resonance imaging, we found that personally familiar faces engage the macaque face-processing network more than unfamiliar faces. Familiar faces also recruited two hitherto unknown face areas at anatomically conserved locations within the perirhinal cortex and the temporal pole. These two areas, but not the core face-processing network, responded to familiar faces emerging from a blur with a characteristic nonlinear surge, akin to the abruptness of familiar face recognition.


Control of species-dependent cortico-motoneuronal connections underlying manual dexterity

Science

Superior manual dexterity in higher primates emerged together with the appearance of cortico-motoneuronal (CM) connections during the evolution of the mammalian corticospinal (CS) system. Previously thought to be specific to higher primates, we identified transient CM connections in early postnatal mice, which are eventually eliminated by Sema6D-PlexA1 signaling. PlexA1 mutant mice maintain CM connections into adulthood and exhibit superior manual dexterity as compared with that of controls. Thus, species-dependent regulation of PlexA1 expression may have been crucial in the evolution of mammalian CS systems that improved fine motor control in higher primates.


CubeSat networks hasten shift to commercial weather data

Science

Gathering the global atmospheric data that go into weather forecasts has long been the job of big, costly, government-run satellites. But on 14 July, the scheduled launch of a Russian Soyuz rocket could signal the shift toward a different model, in which some of the data come from swarms of small private satellites called CubeSats. Among the dozens of CubeSats on the rocket will be 11 tiny weather satellites--eight from Glasgow, U.K.–based Spire Global, and three from GeoOptics, based in Pasadena, California. They will boost the companies' in-orbit constellations to 40 and four, respectively--giving them the chance to compete in a forthcoming pilot program, in which the National Oceanic and Atmospheric Administration will buy weather data from them to supplement the information obtained from the usual array of multibillion-dollar satellites.


AI in Action: Neural networks learn the art of chemical synthesis

Science

Chemists looking to cook up new molecules face a challenge of choosing among hundreds of potential molecular building blocks and thousands of chemical reactions for linking them together. Computational chemists have long programmed computers with known chemical reactions, hoping to create software able to calculate successful molecular recipes. But reactions often don't work in a binary way, being either successful or not. Instead of programming reactions as hard and fast rules, researchers have developed a neural network that learns from millions successful experiments and figures out on its own which reactions to choose to put together new molecules.