Plants that grow in the ground make all their carbon-based infrastructure from carbon dioxide (CO2). By contrast, plants built by chemists use petroleum and natural gas as their carbon feedstock. In a review, De Luna et al. explore the prospective challenges and opportunities for manufacturing commodity chemicals such as ethylene and alcohols by direct electrochemical reduction of CO2. They estimate that production costs would be competitive with fossil technologies if renewable electricity costs drop below 4 cents per kilowatt-hour and electrical-to-chemical conversion efficiencies reach 60%. As the world continues to transition toward carbon emissions–free energy technologies, there remains a need to also reduce the carbon emissions of the chemical production industry. Today many of the world's chemicals are produced from fossil fuel–derived feedstocks. Electrochemical conversion of carbon dioxide (CO2) into chemical feedstocks offers a way to turn waste emissions into valuable products, closing the carbon loop. When coupled to renewable sources of electricity, these products can be made with a net negative carbon emissions footprint, helping to sequester CO2 into usable goods. Research and development into electrocatalytic materials for CO2 reduction has intensified in recent years, with advances in selectivity, efficiency, and reaction rate progressing toward practical implementation. A variety of chemical products can be made from CO2, such as alcohols, oxygenates, synthesis gas (syngas), and olefins--staples in the global chemical industry. Because these products are produced at substantial scale, a switch to renewably powered production could result in a substantial carbon emissions reduction impact. The advancement of electrochemical technology to convert electrons generated from renewable power into stable chemical form also represents one avenue to long-term (e.g., seasonal) storage of energy. The science of electrocatalytic CO2 reduction continues to progress, with priority given to the need to pinpoint more accurately the targets for practical application, the economics of chemical products, and barriers to market entry.
Machine learning can synthesize "almost-but-not-quite replica data" based on real data, facilitating research and data sharing while protecting privacy of the real data, but inconsistent data protection laws can stymie use of this approach. Removal of key information from data can enhance privacy, but this limits data utility and fuels an arms race between deidentification and reidentification. Instead, a generative adversarial network can synthesize data that mimic a protected dataset for analytical purposes but are less likely to reveal any actual private information. Bellovin et al. recommend amendments to privacy statutes that are often too absolute and fail to recognize the protections and analytical potential of this approach.
Di Carlo et al. comment that our original results were insufficient to prove that the ghost cytometry technique is performing a morphologic analysis of cells in flow. We emphasize that the technique is primarily intended to acquire and classify morphological information of cells in a computationally efficient manner without reconstructing images. We provide additional supporting information, including images reconstructed from the compressive waveforms and a discussion of current and future throughput potentials. Ghost cytometry (GC) performs a direct analysis of compressive imaging waveforms and thereby substantially relieves the computational bottleneck hindering the realization of high-throughput cytometry based on morphological information (1). The comments by Di Carlo et al. argue against a number of our conclusions (2), but given the restricted length allowed for this response, we will address what we consider the most important points.
Ota et al. (Reports, 15 June 2018, p. 1246) report using pseudo-random optical masks and a spatial-temporal transformation to perform blur-free, high–frame rate imaging of cells in flow with a high signal-to-noise ratio. They also claim sorting at rates of 3000 cells per second, based on imaging data. The experiments conducted and results reported in their study are insufficient to support these conclusions. Ota et al. (1) proposed an approach to perform image-based flow cytometry and cell sorting that has attracted substantial attention because high throughput ( 3000 cells/s) and a high signal-to-noise ratio (SNR) were claimed. For example, on the basis of these assertions, the introductory commentary (2) referred to the system as an "ultrahigh-speed fluorescence imaging–activated cell sorter."
Service robots could assist people with severe disabilities to go beyond basic communication and movement enabled by current devices, but they would require an efficient and minimalist control system. Kuhner et al. developed a robotic service assistant that performs complex tasks in real-world environments and is controlled using thought. The robot can fetch and carry objects and also interact in close physical proximity to the user. This control is achieved by combining techniques from brain-signal decoding and natural language processing, where common terminology is used to maximize the overlap between the way the user sees the world and the way the task planner defines and controls each primitive action for the robot. This is an article distributed under the terms of the Science Journals Default License.
Like engineers who characterize the fidelity of signals flowing through a circuit, neuroscientists focus on quantifying the degree to which neuronal signals are "noisy" (1, 2). Engineers have the benefit of designing the system and knowing the form of the signal, making identification of corrupting noise relatively straightforward. For neuroscientists, the task is harder, as it entails figuring out first what the signal is, and only then, what the noise is. On pages 254, 253, and 255 of this issue, Gründemann et al. (3), Allen et al. (4), and Stringer et al. (5), respectively, report findings from large-scale neural recordings in the brains of mice and find brainwide activity that correlates with behavior that might usually be ignored as noise. These studies prompt reconsideration of the origin and impacts of "noise" in the nervous system.
Space is the final frontier for understanding how extreme environments affect human physiology. Following twin astronauts, one of which spent a year-long mission on the International Space Station, Garrett-Bakelman et al. examined molecular and physiological traits that may be affected by time in space (see the Perspective by Löbrich and Jeggo). Sequencing the components of whole blood revealed that the length of telomeres, which is important to maintain in dividing cells and may be related to human aging, changed substantially during space flight and again upon return to Earth. Coupled with changes in DNA methylation in immune cells and cardiovascular and cognitive effects, this study provides a basis to assess the hazards of long-term space habitation. Science, this issue p. eaau8650; see also p. 127 To date, 559 humans have been flown into space, but long-duration ( 300 days) missions are rare (n 8 total). Long-duration missions that will take humans to Mars and beyond are planned ...
A better understanding of the mechanisms underlying the action of antidepressants is urgently needed. Moda-Sava et al. explored a possible mode of action for the drug ketamine, which has recently been shown to help patients recover from depression (see the Perspective by Beyeler). Ketamine rescued behavior in mice that was associated with depression-like phenotypes by selectively reversing stress-induced spine loss and restoring coordinated multicellular ensemble activity in prefrontal microcircuits. The initial induction of ketamine's antidepressant effect on mouse behavior occurred independently of effects on spine formation. Instead, synaptogenesis in the prefrontal region played a critical role in nourishing these effects over time. Interventions aimed at enhancing the survival of restored synapses may thus be useful for sustaining the behavioral effects of fast-acting antidepressants. Science, this issue p. eaat8078; see also p. 129 Depression is an episodic form of mental illness, yet the circuit-level mechanisms driving the induction, remission, and recurrence of depressive episodes over time are not well understood. Ketamine relieves depressive symptoms rapidly, providing an opportunity to study the neurobiological substrates of transitions from depression to remission and to test whether mechanisms that induce antidepressant effects acutely are distinct from those that sustain them. Contrasting changes in dendritic spine density in prefrontal cortical pyramidal cells have been associated with the emergence of depression-related behaviors in chronic stress models and with ketamine's antidepressant effects.
In science news around the world, Sydney Brenner, the Nobel laureate who made seminal discoveries in genetics and developmental biology, dies at age 92. Japan's Hayabusa2 mission continues its novel exploration of the asteroid Ryugu by blowing a crater in it so the spacecraft can collect samples; scientists are eager to study material from beneath the surface that has not undergone eons of space weathering. The U.S. National Institutes of Health has begun to restrict visitors from certain countries at its campus in Bethesda, Maryland, for national security reasons, sparking concerns from its staff scientists. Only 10 days after Google created an eight-member external advisory council on the ethics of artificial intelligence research, the company pulled the plug last week amid controversy over the views and affiliations of the council's members. The use of chemicals to disperse oil spills largely doesn't create a mixture more toxic than the oil itself, the U.S. National Academy of Sciences reports.