Showing papers in "Proceedings of the National Academy of Sciences of the United States of America in 2017"

Overcoming catastrophic forgetting in neural networks

Abstract: The ability to learn tasks in a sequential fashion is crucial to the development of artificial intelligence. Until now neural networks have not been capable of this and it has been widely thought that catastrophic forgetting is an inevitable feature of connectionist models. We show that it is possible to overcome this limitation and train networks that can maintain expertise on tasks that they have not experienced for a long time. Our approach remembers old tasks by selectively slowing down learning on the weights important for those tasks. We demonstrate our approach is scalable and effective by solving a set of classification tasks based on a hand-written digit dataset and by learning several Atari 2600 games sequentially.

Biological annihilation via the ongoing sixth mass extinction signaled by vertebrate population losses and declines

Abstract: The population extinction pulse we describe here shows, from a quantitative viewpoint, that Earth’s sixth mass extinction is more severe than perceived when looking exclusively at species extinctions. Therefore, humanity needs to address anthropogenic population extirpation and decimation immediately. That conclusion is based on analyses of the numbers and degrees of range contraction (indicative of population shrinkage and/or population extinctions according to the International Union for Conservation of Nature) using a sample of 27,600 vertebrate species, and on a more detailed analysis documenting the population extinctions between 1900 and 2015 in 177 mammal species. We find that the rate of population loss in terrestrial vertebrates is extremely high—even in “species of low concern.” In our sample, comprising nearly half of known vertebrate species, 32% (8,851/27,600) are decreasing; that is, they have decreased in population size and range. In the 177 mammals for which we have detailed data, all have lost 30% or more of their geographic ranges and more than 40% of the species have experienced severe population declines (>80% range shrinkage). Our data indicate that beyond global species extinctions Earth is experiencing a huge episode of population declines and extirpations, which will have negative cascading consequences on ecosystem functioning and services vital to sustaining civilization. We describe this as a “biological annihilation” to highlight the current magnitude of Earth’s ongoing sixth major extinction event.

Natural climate solutions

Abstract: Better stewardship of land is needed to achieve the Paris Climate Agreement goal of holding warming to below 2 °C; however, confusion persists about the specific set of land stewardship options available and their mitigation potential. To address this, we identify and quantify "natural climate solutions" (NCS): 20 conservation, restoration, and improved land management actions that increase carbon storage and/or avoid greenhouse gas emissions across global forests, wetlands, grasslands, and agricultural lands. We find that the maximum potential of NCS-when constrained by food security, fiber security, and biodiversity conservation-is 23.8 petagrams of CO2 equivalent (PgCO2e) y-1 (95% CI 20.3-37.4). This is ≥30% higher than prior estimates, which did not include the full range of options and safeguards considered here. About half of this maximum (11.3 PgCO2e y-1) represents cost-effective climate mitigation, assuming the social cost of CO2 pollution is ≥100 USD MgCO2e-1 by 2030. Natural climate solutions can provide 37% of cost-effective CO2 mitigation needed through 2030 for a >66% chance of holding warming to below 2 °C. One-third of this cost-effective NCS mitigation can be delivered at or below 10 USD MgCO2-1 Most NCS actions-if effectively implemented-also offer water filtration, flood buffering, soil health, biodiversity habitat, and enhanced climate resilience. Work remains to better constrain uncertainty of NCS mitigation estimates. Nevertheless, existing knowledge reported here provides a robust basis for immediate global action to improve ecosystem stewardship as a major solution to climate change.

Temperature increase reduces global yields of major crops in four independent estimates

Abstract: Wheat, rice, maize, and soybean provide two-thirds of human caloric intake. Assessing the impact of global temperature increase on production of these crops is therefore critical to maintaining global food supply, but different studies have yielded different results. Here, we investigated the impacts of temperature on yields of the four crops by compiling extensive published results from four analytical methods: global grid-based and local point-based models, statistical regressions, and field-warming experiments. Results from the different methods consistently showed negative temperature impacts on crop yield at the global scale, generally underpinned by similar impacts at country and site scales. Without CO2 fertilization, effective adaptation, and genetic improvement, each degree-Celsius increase in global mean temperature would, on average, reduce global yields of wheat by 6.0%, rice by 3.2%, maize by 7.4%, and soybean by 3.1%. Results are highly heterogeneous across crops and geographical areas, with some positive impact estimates. Multimethod analyses improved the confidence in assessments of future climate impacts on global major crops and suggest crop- and region-specific adaptation strategies to ensure food security for an increasing world population.

Catalytic oxidation of Li2S on the surface of metal sulfides for Li−S batteries

Abstract: Polysulfide binding and trapping to prevent dissolution into the electrolyte by a variety of materials has been well studied in Li−S batteries. Here we discover that some of those materials can play an important role as an activation catalyst to facilitate oxidation of the discharge product, Li2S, back to the charge product, sulfur. Combining theoretical calculations and experimental design, we select a series of metal sulfides as a model system to identify the key parameters in determining the energy barrier for Li2S oxidation and polysulfide adsorption. We demonstrate that the Li2S decomposition energy barrier is associated with the binding between isolated Li ions and the sulfur in sulfides; this is the main reason that sulfide materials can induce lower overpotential compared with commonly used carbon materials. Fundamental understanding of this reaction process is a crucial step toward rational design and screening of materials to achieve high reversible capacity and long cycle life in Li−S batteries.

On-demand high-capacity ride-sharing via dynamic trip-vehicle assignment

Abstract: Ride-sharing services are transforming urban mobility by providing timely and convenient transportation to anybody, anywhere, and anytime. These services present enormous potential for positive societal impacts with respect to pollution, energy consumption, congestion, etc. Current mathematical models, however, do not fully address the potential of ride-sharing. Recently, a large-scale study highlighted some of the benefits of car pooling but was limited to static routes with two riders per vehicle (optimally) or three (with heuristics). We present a more general mathematical model for real-time high-capacity ride-sharing that (i) scales to large numbers of passengers and trips and (ii) dynamically generates optimal routes with respect to online demand and vehicle locations. The algorithm starts from a greedy assignment and improves it through a constrained optimization, quickly returning solutions of good quality and converging to the optimal assignment over time. We quantify experimentally the tradeoff between fleet size, capacity, waiting time, travel delay, and operational costs for low- to medium-capacity vehicles, such as taxis and van shuttles. The algorithm is validated with ∼3 million rides extracted from the New York City taxicab public dataset. Our experimental study considers ride-sharing with rider capacity of up to 10 simultaneous passengers per vehicle. The algorithm applies to fleets of autonomous vehicles and also incorporates rebalancing of idling vehicles to areas of high demand. This framework is general and can be used for many real-time multivehicle, multitask assignment problems.

Immunogenicity and structures of a rationally designed prefusion MERS-CoV spike antigen

Abstract: Middle East respiratory syndrome coronavirus (MERS-CoV) is a lineage C betacoronavirus that since its emergence in 2012 has caused outbreaks in human populations with case-fatality rates of ∼36%. As in other coronaviruses, the spike (S) glycoprotein of MERS-CoV mediates receptor recognition and membrane fusion and is the primary target of the humoral immune response during infection. Here we use structure-based design to develop a generalizable strategy for retaining coronavirus S proteins in the antigenically optimal prefusion conformation and demonstrate that our engineered immunogen is able to elicit high neutralizing antibody titers against MERS-CoV. We also determined high-resolution structures of the trimeric MERS-CoV S ectodomain in complex with G4, a stem-directed neutralizing antibody. The structures reveal that G4 recognizes a glycosylated loop that is variable among coronaviruses and they define four conformational states of the trimer wherein each receptor-binding domain is either tightly packed at the membrane-distal apex or rotated into a receptor-accessible conformation. Our studies suggest a potential mechanism for fusion initiation through sequential receptor-binding events and provide a foundation for the structure-based design of coronavirus vaccines.

Future urban land expansion and implications for global croplands.

Abstract: Urban expansion often occurs on croplands. However, there is little scientific understanding of how global patterns of future urban expansion will affect the world's cultivated areas. Here, we combine spatially explicit projections of urban expansion with datasets on global croplands and crop yields. Our results show that urban expansion will result in a 1.8-2.4% loss of global croplands by 2030, with substantial regional disparities. About 80% of global cropland loss from urban expansion will take place in Asia and Africa. In both Asia and Africa, much of the cropland that will be lost is more than twice as productive as national averages. Asia will experience the highest absolute loss in cropland, whereas African countries will experience the highest percentage loss of cropland. Globally, the croplands that are likely to be lost were responsible for 3-4% of worldwide crop production in 2000. Urban expansion is expected to take place on cropland that is 1.77 times more productive than the global average. The loss of cropland is likely to be accompanied by other sustainability risks and threatens livelihoods, with diverging characteristics for different megaurban regions. Governance of urban area expansion thus emerges as a key area for securing livelihoods in the agrarian economies of the Global South.

Revisiting the social cost of carbon

Abstract: The social cost of carbon (SCC) is a central concept for understanding and implementing climate change policies. This term represents the economic cost caused by an additional ton of carbon dioxide emissions or its equivalent. The present study presents updated estimates based on a revised DICE model (Dynamic Integrated model of Climate and the Economy). The study estimates that the SCC is $31 per ton of CO2 in 2010 US$ for the current period (2015). For the central case, the real SCC grows at 3% per year over the period to 2050. The paper also compares the estimates with those from other sources.

Soil carbon debt of 12,000 years of human land use

Abstract: Human appropriation of land for agriculture has greatly altered the terrestrial carbon balance, creating a large but uncertain carbon debt in soils. Estimating the size and spatial distribution of soil organic carbon (SOC) loss due to land use and land cover change has been difficult but is a critical step in understanding whether SOC sequestration can be an effective climate mitigation strategy. In this study, a machine learning-based model was fitted using a global compilation of SOC data and the History Database of the Global Environment (HYDE) land use data in combination with climatic, landform and lithology covariates. Model results compared favorably with a global compilation of paired plot studies. Projection of this model onto a world without agriculture indicated a global carbon debt due to agriculture of 133 Pg C for the top 2 m of soil, with the rate of loss increasing dramatically in the past 200 years. The HYDE classes “grazing” and “cropland” contributed nearly equally to the loss of SOC. There were higher percent SOC losses on cropland but since more than twice as much land is grazed, slightly higher total losses were found from grazing land. Important spatial patterns of SOC loss were found: Hotspots of SOC loss coincided with some major cropping regions as well as semiarid grazing regions, while other major agricultural zones showed small losses and even net gains in SOC. This analysis has demonstrated that there are identifiable regions which can be targeted for SOC restoration efforts.

Gut bacteria from multiple sclerosis patients modulate human T cells and exacerbate symptoms in mouse models.

Abstract: The gut microbiota regulates T cell functions throughout the body. We hypothesized that intestinal bacteria impact the pathogenesis of multiple sclerosis (MS), an autoimmune disorder of the CNS and thus analyzed the microbiomes of 71 MS patients not undergoing treatment and 71 healthy controls. Although no major shifts in microbial community structure were found, we identified specific bacterial taxa that were significantly associated with MS. Akkermansia muciniphila and Acinetobacter calcoaceticus, both increased in MS patients, induced proinflammatory responses in human peripheral blood mononuclear cells and in monocolonized mice. In contrast, Parabacteroides distasonis, which was reduced in MS patients, stimulated antiinflammatory IL-10–expressing human CD4+CD25+ T cells and IL-10+FoxP3+ Tregs in mice. Finally, microbiota transplants from MS patients into germ-free mice resulted in more severe symptoms of experimental autoimmune encephalomyelitis and reduced proportions of IL-10+ Tregs compared with mice “humanized” with microbiota from healthy controls. This study identifies specific human gut bacteria that regulate adaptive autoimmune responses, suggesting therapeutic targeting of the microbiota as a treatment for MS.

An anion-immobilized composite electrolyte for dendrite-free lithium metal anodes

Abstract: Lithium metal is strongly regarded as a promising electrode material in next-generation rechargeable batteries due to its extremely high theoretical specific capacity and lowest reduction potential. However, the safety issue and short lifespan induced by uncontrolled dendrite growth have hindered the practical applications of lithium metal anodes. Hence, we propose a flexible anion-immobilized ceramic–polymer composite electrolyte to inhibit lithium dendrites and construct safe batteries. Anions in the composite electrolyte are tethered by a polymer matrix and ceramic fillers, inducing a uniform distribution of space charges and lithium ions that contributes to a dendrite-free lithium deposition. The dissociation of anions and lithium ions also helps to reduce the polymer crystallinity, rendering stable and fast transportation of lithium ions. Ceramic fillers in the electrolyte extend the electrochemically stable window to as wide as 5.5 V and provide a barrier to short circuiting for realizing safe batteries at elevated temperature. The anion-immobilized electrolyte can be applied in all–solid-state batteries and exhibits a small polarization of 15 mV. Cooperated with LiFePO 4 and LiNi 0.5 Co 0.2 Mn 0.3 O 2 cathodes, the all–solid-state lithium metal batteries render excellent specific capacities of above 150 mAh⋅g −1 and well withstand mechanical bending. These results reveal a promising opportunity for safe and flexible next-generation lithium metal batteries.

Multispecies coalescent delimits structure, not species

Abstract: The multispecies coalescent model underlies many approaches used for species delimitation. In previous work assessing the performance of species delimitation under this model, speciation was treated as an instantaneous event rather than as an extended process involving distinct phases of speciation initiation (structuring) and completion. Here, we use data under simulations that explicitly model speciation as an extended process rather than an instantaneous event and carry out species delimitation inference on these data under the multispecies coalescent. We show that the multispecies coalescent diagnoses genetic structure, not species, and that it does not statistically distinguish structure associated with population isolation vs. species boundaries. Because of the misidentification of population structure as putative species, our work raises questions about the practice of genome-based species discovery, with cascading consequences in other fields. Specifically, all fields that rely on species as units of analysis, from conservation biology to studies of macroevolutionary dynamics, will be impacted by inflated estimates of the number of species, especially as genomic resources provide unprecedented power for detecting increasingly finer-scaled genetic structure under the multispecies coalescent. As such, our work also represents a general call for systematic study to reconsider a reliance on genomic data alone. Until new methods are developed that can discriminate between structure due to population-level processes and that due to species boundaries, genomic-based results should only be considered a hypothesis that requires validation of delimited species with multiple data types, such as phenotypic and ecological information.

Hydrologic regulation of plant rooting depth

Abstract: Plant rooting depth affects ecosystem resilience to environmental stress such as drought. Deep roots connect deep soil/groundwater to the atmosphere, thus influencing the hydrologic cycle and climate. Deep roots enhance bedrock weathering, thus regulating the long-term carbon cycle. However, we know little about how deep roots go and why. Here, we present a global synthesis of 2,200 root observations of >1,000 species along biotic (life form, genus) and abiotic (precipitation, soil, drainage) gradients. Results reveal strong sensitivities of rooting depth to local soil water profiles determined by precipitation infiltration depth from the top (reflecting climate and soil), and groundwater table depth from below (reflecting topography-driven land drainage). In well-drained uplands, rooting depth follows infiltration depth; in waterlogged lowlands, roots stay shallow, avoiding oxygen stress below the water table; in between, high productivity and drought can send roots many meters down to the groundwater capillary fringe. This framework explains the contrasting rooting depths observed under the same climate for the same species but at distinct topographic positions. We assess the global significance of these hydrologic mechanisms by estimating root water-uptake depths using an inverse model, based on observed productivity and atmosphere, at 30″ (∼1-km) global grids to capture the topography critical to soil hydrology. The resulting patterns of plant rooting depth bear a strong topographic and hydrologic signature at landscape to global scales. They underscore a fundamental plant–water feedback pathway that may be critical to understanding plant-mediated global change.

cGAS is essential for cellular senescence

Abstract: Cellular senescence is a natural barrier to tumorigenesis and it contributes to the antitumor effects of several therapies, including radiation and chemotherapeutic drugs. Senescence also plays an important role in aging, fibrosis, and tissue repair. The DNA damage response is a key event leading to senescence, which is characterized by the senescence-associated secretory phenotype (SASP) that includes expression of inflammatory cytokines. Here we show that cGMP-AMP (cGAMP) synthase (cGAS), a cytosolic DNA sensor that activates innate immunity, is essential for senescence. Deletion of cGAS accelerated the spontaneous immortalization of mouse embryonic fibroblasts. cGAS deletion also abrogated SASP induced by spontaneous immortalization or DNA damaging agents, including radiation and etoposide. cGAS is localized in the cytoplasm of nondividing cells but enters the nucleus and associates with chromatin DNA during mitosis in proliferating cells. DNA damage leads to accumulation of damaged DNA in cytoplasmic foci that contain cGAS. In human lung adenocarcinoma patients, low expression of cGAS is correlated with poor survival. These results indicate that cGAS mediates cellular senescence and retards immortalization. This is distinct from, and complementary to, the role of cGAS in activating antitumor immunity.

Elucidating reaction mechanisms on quantum computers

Abstract: With rapid recent advances in quantum technology, we are close to the threshold of quantum devices whose computational powers can exceed those of classical supercomputers. Here, we show that a quantum computer can be used to elucidate reaction mechanisms in complex chemical systems, using the open problem of biological nitrogen fixation in nitrogenase as an example. We discuss how quantum computers can augment classical computer simulations used to probe these reaction mechanisms, to significantly increase their accuracy and enable hitherto intractable simulations. Our resource estimates show that, even when taking into account the substantial overhead of quantum error correction, and the need to compile into discrete gate sets, the necessary computations can be performed in reasonable time on small quantum computers. Our results demonstrate that quantum computers will be able to tackle important problems in chemistry without requiring exorbitant resources.

Potential high-Tc superconducting lanthanum and yttrium hydrides at high pressure.

Abstract: A systematic structure search in the La–H and Y–H systems under pressure reveals some hydrogen-rich structures with intriguing electronic properties. For example, LaH10 is found to adopt a sodalite-like face-centered cubic (fcc) structure, stable above 200 GPa, and LaH8 a C2/m space group structure. Phonon calculations indicate both are dynamically stable; electron phonon calculations coupled to Bardeen–Cooper–Schrieffer (BCS) arguments indicate they might be high-Tc superconductors. In particular, the superconducting transition temperature Tc calculated for LaH10 is 274–286 K at 210 GPa. Similar calculations for the Y–H system predict stability of the sodalite-like fcc YH10 and a Tc above room temperature, reaching 305–326 K at 250 GPa. The study suggests that dense hydrides consisting of these and related hydrogen polyhedral networks may represent new classes of potential very high-temperature superconductors.

Gut microbiota from multiple sclerosis patients enables spontaneous autoimmune encephalomyelitis in mice.

Abstract: There is emerging evidence that the commensal microbiota has a role in the pathogenesis of multiple sclerosis (MS), a putative autoimmune disease of the CNS. Here, we compared the gut microbial composition of 34 monozygotic twin pairs discordant for MS. While there were no major differences in the overall microbial profiles, we found a significant increase in some taxa such as Akkermansia in untreated MS twins. Furthermore, most notably, when transplanted to a transgenic mouse model of spontaneous brain autoimmunity, MS twin-derived microbiota induced a significantly higher incidence of autoimmunity than the healthy twin-derived microbiota. The microbial profiles of the colonized mice showed a high intraindividual and remarkable temporal stability with several differences, including Sutterella, an organism shown to induce a protective immunoregulatory profile in vitro. Immune cells from mouse recipients of MS-twin samples produced less IL-10 than immune cells from mice colonized with healthy-twin samples. IL-10 may have a regulatory role in spontaneous CNS autoimmunity, as neutralization of the cytokine in mice colonized with healthy-twin fecal samples increased disease incidence. These findings provide evidence that MS-derived microbiota contain factors that precipitate an MS-like autoimmune disease in a transgenic mouse model. They hence encourage the detailed search for protective and pathogenic microbial components in human MS.

Isolation of exosomes from whole blood by integrating acoustics and microfluidics

Abstract: Exosomes are nanoscale extracellular vesicles that play an important role in many biological processes, including intercellular communications, antigen presentation, and the transport of proteins, RNA, and other molecules. Recently there has been significant interest in exosome-related fundamental research, seeking new exosome-based biomarkers for health monitoring and disease diagnoses. Here, we report a separation method based on acoustofluidics (i.e., the integration of acoustics and microfluidics) to isolate exosomes directly from whole blood in a label-free and contact-free manner. This acoustofluidic platform consists of two modules: a microscale cell-removal module that first removes larger blood components, followed by extracellular vesicle subgroup separation in the exosome-isolation module. In the cell-removal module, we demonstrate the isolation of 110-nm particles from a mixture of micro- and nanosized particles with a yield greater than 99%. In the exosome-isolation module, we isolate exosomes from an extracellular vesicle mixture with a purity of 98.4%. Integrating the two acoustofluidic modules onto a single chip, we isolated exosomes from whole blood with a blood cell removal rate of over 99.999%. With its ability to perform rapid, biocompatible, label-free, contact-free, and continuous-flow exosome isolation, the integrated acoustofluidic device offers a unique approach to investigate the role of exosomes in the onset and progression of human diseases with potential applications in health monitoring, medical diagnosis, targeted drug delivery, and personalized medicine.

Brain network dynamics are hierarchically organized in time

Abstract: The brain recruits neuronal populations in a temporally coordinated manner in task and at rest. However, the extent to which large-scale networks exhibit their own organized temporal dynamics is unclear. We use an approach designed to find repeating network patterns in whole-brain resting fMRI data, where networks are defined as graphs of interacting brain areas. We find that the transitions between networks are nonrandom, with certain networks more likely to occur after others. Further, this nonrandom sequencing is itself hierarchically organized, revealing two distinct sets of networks, or metastates, that the brain has a tendency to cycle within. One metastate is associated with sensory and motor regions, and the other involves areas related to higher order cognition. Moreover, we find that the proportion of time that a subject spends in each brain network and metastate is a consistent subject-specific measure, is heritable, and shows a significant relationship with cognitive traits.

Knee osteoarthritis has doubled in prevalence since the mid-20th century

Abstract: Knee osteoarthritis (OA) is believed to be highly prevalent today because of recent increases in life expectancy and body mass index (BMI), but this assumption has not been tested using long-term historical or evolutionary data. We analyzed long-term trends in knee OA prevalence in the United States using cadaver-derived skeletons of people aged ≥50 y whose BMI at death was documented and who lived during the early industrial era (1800s to early 1900s; n = 1,581) and the modern postindustrial era (late 1900s to early 2000s; n = 819). Knee OA among individuals estimated to be ≥50 y old was also assessed in archeologically derived skeletons of prehistoric hunter-gatherers and early farmers (6000-300 B.P.; n = 176). OA was diagnosed based on the presence of eburnation (polish from bone-on-bone contact). Overall, knee OA prevalence was found to be 16% among the postindustrial sample but only 6% and 8% among the early industrial and prehistoric samples, respectively. After controlling for age, BMI, and other variables, knee OA prevalence was 2.1-fold higher (95% confidence interval, 1.5-3.1) in the postindustrial sample than in the early industrial sample. Our results indicate that increases in longevity and BMI are insufficient to explain the approximate doubling of knee OA prevalence that has occurred in the United States since the mid-20th century. Knee OA is thus more preventable than is commonly assumed, but prevention will require research on additional independent risk factors that either arose or have become amplified in the postindustrial era.

Human-started wildfires expand the fire niche across the United States

Abstract: The economic and ecological costs of wildfire in the United States have risen substantially in recent decades. Although climate change has likely enabled a portion of the increase in wildfire activity, the direct role of people in increasing wildfire activity has been largely overlooked. We evaluate over 1.5 million government records of wildfires that had to be extinguished or managed by state or federal agencies from 1992 to 2012, and examined geographic and seasonal extents of human-ignited wildfires relative to lightning-ignited wildfires. Humans have vastly expanded the spatial and seasonal "fire niche" in the coterminous United States, accounting for 84% of all wildfires and 44% of total area burned. During the 21-y time period, the human-caused fire season was three times longer than the lightning-caused fire season and added an average of 40,000 wildfires per year across the United States. Human-started wildfires disproportionally occurred where fuel moisture was higher than lightning-started fires, thereby helping expand the geographic and seasonal niche of wildfire. Human-started wildfires were dominant (>80% of ignitions) in over 5.1 million km2, the vast majority of the United States, whereas lightning-started fires were dominant in only 0.7 million km2, primarily in sparsely populated areas of the mountainous western United States. Ignitions caused by human activities are a substantial driver of overall fire risk to ecosystems and economies. Actions to raise awareness and increase management in regions prone to human-started wildfires should be a focus of United States policy to reduce fire risk and associated hazards.

Multisensor-integrated organs-on-chips platform for automated and continual in situ monitoring of organoid behaviors

Abstract: Organ-on-a-chip systems are miniaturized microfluidic 3D human tissue and organ models designed to recapitulate the important biological and physiological parameters of their in vivo counterparts. They have recently emerged as a viable platform for personalized medicine and drug screening. These in vitro models, featuring biomimetic compositions, architectures, and functions, are expected to replace the conventional planar, static cell cultures and bridge the gap between the currently used preclinical animal models and the human body. Multiple organoid models may be further connected together through the microfluidics in a similar manner in which they are arranged in vivo, providing the capability to analyze multiorgan interactions. Although a wide variety of human organ-on-a-chip models have been created, there are limited efforts on the integration of multisensor systems. However, in situ continual measuring is critical in precise assessment of the microenvironment parameters and the dynamic responses of the organs to pharmaceutical compounds over extended periods of time. In addition, automated and noninvasive capability is strongly desired for long-term monitoring. Here, we report a fully integrated modular physical, biochemical, and optical sensing platform through a fluidics-routing breadboard, which operates organ-on-a-chip units in a continual, dynamic, and automated manner. We believe that this platform technology has paved a potential avenue to promote the performance of current organ-on-a-chip models in drug screening by integrating a multitude of real-time sensors to achieve automated in situ monitoring of biophysical and biochemical parameters.

Proliferation of PD-1+ CD8 T cells in peripheral blood after PD-1-targeted therapy in lung cancer patients.

Abstract: Exhausted T cells in chronic infections and cancer have sustained expression of the inhibitory receptor programmed cell death 1 (PD-1). Therapies that block the PD-1 pathway have shown promising clinical results in a significant number of advanced-stage cancer patients. Nonetheless, a better understanding of the immunological responses induced by PD-1 blockade in cancer patients is lacking. Identification of predictive biomarkers is a priority in the field, but whether peripheral blood analysis can provide biomarkers to monitor or predict patients’ responses to treatment remains to be resolved. In this study, we analyzed longitudinal blood samples from advanced stage non–small cell lung cancer (NSCLC) patients (n = 29) receiving PD-1–targeted therapies. We detected an increase in Ki-67+ PD-1+ CD8 T cells following therapy in ∼70% of patients, and most responses were induced after the first or second treatment cycle. This T-cell activation was not indiscriminate because we observed only minimal effects on EBV-specific CD8 T cells, suggesting that responding cells may be tumor specific. These proliferating CD8 T cells had an effector-like phenotype (HLA-DR+, CD38+, Bcl-2lo), expressed costimulatory molecules (CD28, CD27, ICOS), and had high levels of PD-1 and coexpression of CTLA-4. We found that 70% of patients with disease progression had either a delayed or absent PD-1+ CD8 T-cell response, whereas 80% of patients with clinical benefit exhibited PD-1+ CD8 T-cell responses within 4 wk of treatment initiation. Our results suggest that peripheral blood analysis may provide valuable insights into NSCLC patients’ responses to PD-1–targeted therapies.

Autonomous sweat extraction and analysis applied to cystic fibrosis and glucose monitoring using a fully integrated wearable platform

Abstract: Perspiration-based wearable biosensors facilitate continuous monitoring of individuals’ health states with real-time and molecular-level insight. The inherent inaccessibility of sweat in sedentary individuals in large volume (≥10 µL) for on-demand and in situ analysis has limited our ability to capitalize on this noninvasive and rich source of information. A wearable and miniaturized iontophoresis interface is an excellent solution to overcome this barrier. The iontophoresis process involves delivery of stimulating agonists to the sweat glands with the aid of an electrical current. The challenge remains in devising an iontophoresis interface that can extract sufficient amount of sweat for robust sensing, without electrode corrosion and burning/causing discomfort in subjects. Here, we overcame this challenge through realizing an electrochemically enhanced iontophoresis interface, integrated in a wearable sweat analysis platform. This interface can be programmed to induce sweat with various secretion profiles for real-time analysis, a capability which can be exploited to advance our knowledge of the sweat gland physiology and the secretion process. To demonstrate the clinical value of our platform, human subject studies were performed in the context of the cystic fibrosis diagnosis and preliminary investigation of the blood/sweat glucose correlation. With our platform, we detected the elevated sweat electrolyte content of cystic fibrosis patients compared with that of healthy control subjects. Furthermore, our results indicate that oral glucose consumption in the fasting state is followed by increased glucose levels in both sweat and blood. Our solution opens the possibility for a broad range of noninvasive diagnostic and general population health monitoring applications.

Experimental Comparison of Two Quantum Computing Architectures

Abstract: We run a selection of algorithms on two state-of-the-art 5-qubit quantum computers that are based on different technology platforms. One is a publicly accessible superconducting transmon device (www.research.ibm.com/ibm-q) with limited connectivity, and the other is a fully connected trapped-ion system. Even though the two systems have different native quantum interactions, both can be programed in a way that is blind to the underlying hardware, thus allowing a comparison of identical quantum algorithms between different physical systems. We show that quantum algorithms and circuits that use more connectivity clearly benefit from a better-connected system of qubits. Although the quantum systems here are not yet large enough to eclipse classical computers, this experiment exposes critical factors of scaling quantum computers, such as qubit connectivity and gate expressivity. In addition, the results suggest that codesigning particular quantum applications with the hardware itself will be paramount in successfully using quantum computers in the future.

Emotion shapes the diffusion of moralized content in social networks

Abstract: Political debate concerning moralized issues is increasingly common in online social networks. However, moral psychology has yet to incorporate the study of social networks to investigate processes by which some moral ideas spread more rapidly or broadly than others. Here, we show that the expression of moral emotion is key for the spread of moral and political ideas in online social networks, a process we call "moral contagion." Using a large sample of social media communications about three polarizing moral/political issues (n = 563,312), we observed that the presence of moral-emotional words in messages increased their diffusion by a factor of 20% for each additional word. Furthermore, we found that moral contagion was bounded by group membership; moral-emotional language increased diffusion more strongly within liberal and conservative networks, and less between them. Our results highlight the importance of emotion in the social transmission of moral ideas and also demonstrate the utility of social network methods for studying morality. These findings offer insights into how people are exposed to moral and political ideas through social networks, thus expanding models of social influence and group polarization as people become increasingly immersed in social media networks.

Tunable moiré bands and strong correlations in small-twist-angle bilayer graphene

Abstract: According to electronic structure theory, bilayer graphene is expected to have anomalous electronic properties when it has long-period moire patterns produced by small misalignments between its individual layer honeycomb lattices. We have realized bilayer graphene moire crystals with accurately controlled twist angles smaller than 1° and studied their properties using scanning probe microscopy and electron transport. We observe conductivity minima at charge neutrality, satellite gaps that appear at anomalous carrier densities for twist angles smaller than 1°, and tunneling densities-of-states that are strongly dependent on carrier density. These features are robust up to large transverse electric fields. In perpendicular magnetic fields, we observe the emergence of a Hofstadter butterfly in the energy spectrum, with fourfold degenerate Landau levels, and broken symmetry quantum Hall states at filling factors ±1, 2, 3. These observations demonstrate that at small twist angles, the electronic properties of bilayer graphene moire crystals are strongly altered by electron-electron interactions.

Adapt to more wildfire in western North American forests as climate changes

Abstract: Wildfires across western North America have increased in number and size over the past three decades, and this trend will continue in response to further warming. As a consequence, the wildland–urban interface is projected to experience substantially higher risk of climate-driven fires in the coming decades. Although many plants, animals, and ecosystem services benefit from fire, it is unknown how ecosystems will respond to increased burning and warming. Policy and management have focused primarily on specified resilience approaches aimed at resistance to wildfire and restoration of areas burned by wildfire through fire suppression and fuels management. These strategies are inadequate to address a new era of western wildfires. In contrast, policies that promote adaptive resilience to wildfire, by which people and ecosystems adjust and reorganize in response to changing fire regimes to reduce future vulnerability, are needed. Key aspects of an adaptive resilience approach are (i) recognizing that fuels reduction cannot alter regional wildfire trends; (ii) targeting fuels reduction to increase adaptation by some ecosystems and residential communities to more frequent fire; (iii) actively managing more wild and prescribed fires with a range of severities; and (iv) incentivizing and planning residential development to withstand inevitable wildfire. These strategies represent a shift in policy and management from restoring ecosystems based on historical baselines to adapting to changing fire regimes and from unsustainable defense of the wildland–urban interface to developing fire-adapted communities. We propose an approach that accepts wildfire as an inevitable catalyst of change and that promotes adaptive responses by ecosystems and residential communities to more warming and wildfire.

Tectonic conformational changes of a coronavirus spike glycoprotein promote membrane fusion

Abstract: The tremendous pandemic potential of coronaviruses was demonstrated twice in the past few decades by two global outbreaks of deadly pneumonia. The coronavirus spike (S) glycoprotein initiates infection by promoting fusion of the viral and cellular membranes through conformational changes that remain largely uncharacterized. Here we report the cryoEM structure of a coronavirus S glycoprotein in the postfusion state, showing large-scale secondary, tertiary, and quaternary rearrangements compared with the prefusion trimer and rationalizing the free-energy landscape of this conformational machine. We also biochemically characterized the molecular events associated with refolding of the metastable prefusion S glycoprotein to the postfusion conformation using limited proteolysis, mass spectrometry, and single-particle EM. The observed similarity between postfusion coronavirus S and paramyxovirus F structures demonstrates that a conserved refolding trajectory mediates entry of these viruses and supports the evolutionary relatedness of their fusion subunits. Finally, our data provide a structural framework for understanding the mode of neutralization of antibodies targeting the fusion machinery and for engineering next-generation subunit vaccines or inhibitors against this medically important virus family.