The 100 most-cited articles in Proceedings of the National Academy of Sciences, 2024

Lipid nanoparticles (LNPs) have recently emerged as a powerful and versatile clinically approved platform for nucleic acid delivery, specifically for mRNA vaccines. A major bottleneck in the field is the release of mRNA-LNPs from the endosomal pathways into the cytosol of cells where they can execute their encoded functions. The data regarding the mechanism of these endosomal escape processes are limited and contradicting. Despite extensive research, there is no consensus regarding the compartment of escape, the cause of the inefficient escape and are currently lacking a robust method to detect the escape. Here, we review the currently known mechanisms of endosomal escape and the available methods to study this process. We critically discuss the limitations and challenges of these methods and the possibilities to overcome these challenges. We propose that the development of currently lacking robust, quantitative high-throughput techniques to study endosomal escape is timely and essential. A better understanding of this process will enable better RNA-LNP designs with improved…

Plastics are now omnipresent in our daily lives. The existence of microplastics (1 µm to 5 mm in length) and possibly even nanoplastics (<1 μm) has recently raised health concerns. In particular, nanoplastics are believed to be more toxic since their smaller size renders them much more amenable, compared to microplastics, to enter the human body. However, detecting nanoplastics imposes tremendous analytical challenges on both the nano-level sensitivity and the plastic-identifying specificity, leading to a knowledge gap in this mysterious nanoworld surrounding us. To address these challenges, we developed a hyperspectral stimulated Raman scattering (SRS) imaging platform with an automated plastic identification algorithm that allows micro-nano plastic analysis at the single-particle level with high chemical specificity and throughput. We first validated the sensitivity enhancement of the narrow band of SRS to enable high-speed single nanoplastic detection below 100 nm. We then devised a data-driven spectral matching algorithm to address spectral identification challenges imposed by…

Antibiotic resistance is a global public health threat. Many factors contribute to this issue, with human antibiotic consumption being significant among them. Analyzing trends and patterns in consumption can aid in developing policies to mitigate the burden of antimicrobial resistance and global disparities in access to antibiotics. Using pharmaceutical sales data licensed from IQVIA, we estimate national-level trends in antibiotic consumption in 67 countries during 2016-2023 and analyze the effects of economic growth and the COVID-19 pandemic. Finally, we estimate global human consumption and project growth through 2030 assuming current trends. We find that estimated antibiotic consumption in reported countries increased 16.3% from 29.5 to 34.3 billion defined daily doses (DDDs) from 2016 to 2023, reflecting a 10.6% increase in the consumption rate from 13.7 to 15.2 DDDs per 1,000 inhabitants per day. Increases were most pronounced in upper-middle- and lower-middle-income countries. While the COVID-19 pandemic significantly reduced consumption globally, this was most pronounced in…

The studies on the origin of versatile oxidation pathways toward targeted pollutants in the single-atom catalysts (SACs)/peroxymonosulfate (PMS) systems were always associated with the coordination structures rather than the perspective of pollutant characteristics, and the analysis of mechanism commonality is lacking. In this work, a variety of single-atom catalysts (M-SACs, M: Fe, Co, and Cu) were fabricated via a pyrolysis process using lignin as the complexation agent and substrate precursor. Sixteen kinds of commonly detected pollutants in various references were selected, and their ln k obs values in M-SACs/PMS systems correlated well ( R 2 = 0.832 to 0.883) with their electrophilic indexes (reflecting the electron accepting/donating ability of the pollutants) as well as the energy gap ( R 2 = 0.801 to 0.840) between the pollutants and M-SACs/PMS complexes. Both the electron transfer process (ETP) and radical pathways can be significantly enhanced in the M-SACs/PMS systems, while radical oxidation was overwhelmed by the ETP oxidation toward the pollutants with lower…

Artificial intelligence that can produce realistic text,images, and other human-like outputs is currently transforming many different industries. Yet it is not yet known how such tools might transform social science research. In the first section of this article, I assess the potential of Generative AI to improve online experiments, agent-based models, and automated content analyses.I also discuss whether these tools may help social scientists perform literature reviews, identify novel research questions, and develop hypotheses to explain them. Next, I evaluate whether Generative AI can help social scientists with more mundane tasks such as acquiring advancedprogramming skills or writing more effective prose. In the second section of this article I discuss the limitations of Generative AI as well as how these tools might be employed by researchers in an ethical manner. I discuss how bias in the processes and data used to train these tools can negatively impact social science research as well as a rangeof other challenges related to accuracy, reproducibility,interpretability, and…

Eleven large language models (LLMs) were assessed using 40 bespoke false-belief tasks, considered a gold standard in testing theory of mind (ToM) in humans. Each task included a false-belief scenario, three closely matched true-belief control scenarios, and the reversed versions of all four. An LLM had to solve all eight scenarios to solve a single task. Older models solved no tasks; Generative Pre-trained Transformer (GPT)-3-davinci-003 (from November 2022) and ChatGPT-3.5-turbo (from March 2023) solved 20% of the tasks; ChatGPT-4 (from June 2023) solved 75% of the tasks, matching the performance of 6-y-old children observed in past studies. We explore the potential interpretation of these results, including the intriguing possibility that ToM-like ability, previously considered unique to humans, may have emerged as an unintended by-product of LLMs' improving language skills. Regardless of how we interpret these outcomes, they signify the advent of more powerful and socially skilled AI-with profound positive and negative implications.

The social and behavioral sciences have been increasingly using automated text analysis to measure psychological constructs in text. We explore whether GPT, the large-language model (LLM) underlying the AI chatbot ChatGPT, can be used as a tool for automated psychological text analysis in several languages. Across 15 datasets ( n = 47,925 manually annotated tweets and news headlines), we tested whether different versions of GPT (3.5 Turbo, 4, and 4 Turbo) can accurately detect psychological constructs (sentiment, discrete emotions, offensiveness, and moral foundations) across 12 languages. We found that GPT ( r = 0.59 to 0.77) performed much better than English-language dictionary analysis ( r = 0.20 to 0.30) at detecting psychological constructs as judged by manual annotators. GPT performed nearly as well as, and sometimes better than, several top-performing fine-tuned machine learning models. Moreover, GPT’s performance improved across successive versions of the model, particularly for lesser-spoken languages, and became less expensive. Overall, GPT may be superior to many…

Aberrant lysine lactylation (Kla) is associated with various diseases which are caused by excessive glycolysis metabolism. However, the regulatory molecules and downstream protein targets of Kla remain largely unclear. Here, we observed a global Kla abundance profile in colorectal cancer (CRC) that negatively correlates with prognosis. Among lactylated proteins detected in CRC, lactylation of eEF1A2K408 resulted in boosted translation elongation and enhanced protein synthesis which contributed to tumorigenesis. By screening eEF1A2 interacting proteins, we identified that KAT8, a lysine acetyltransferase that acted as a pan-Kla writer, was responsible for installing Kla on many protein substrates involving in diverse biological processes. Deletion of KAT8 inhibited CRC tumor growth, especially in a high-lactic tumor microenvironment. Therefore, the KAT8-eEF1A2 Kla axis is utilized to meet increased translational requirements for oncogenic adaptation. As a lactyltransferase, KAT8 may represent a potential therapeutic target for CRC.

We administer a Turing test to AI chatbots. We examine how chatbots behave in a suite of classic behavioral games that are designed to elicit characteristics such as trust, fairness, risk-aversion, cooperation, etc., as well as how they respond to a traditional Big-5 psychological survey that measures personality traits. ChatGPT-4 exhibits behavioral and personality traits that are statistically indistinguishable from a random human from tens of thousands of human subjects from more than 50 countries. Chatbots also modify their behavior based on previous experience and contexts "as if" they were learning from the interactions and change their behavior in response to different framings of the same strategic situation. Their behaviors are often distinct from average and modal human behaviors, in which case they tend to behave on the more altruistic and cooperative end of the distribution. We estimate that they act as if they are maximizing an average of their own and partner's payoffs.

People want to "feel heard" to perceive that they are understood, validated, and valued. Can AI serve the deeply human function of making others feel heard? Our research addresses two fundamental issues: Can AI generate responses that make human recipients feel heard, and how do human recipients react when they believe the response comes from AI? We conducted an experiment and a follow-up study to disentangle the effects of actual source of a message and the presumed source. We found that AI-generated messages made recipients feel more heard than human-generated messages and that AI was better at detecting emotions. However, recipients felt less heard when they realized that a message came from AI (vs. human). Finally, in a follow-up study where the responses were rated by third-party raters, we found that compared with humans, AI demonstrated superior discipline in offering emotional support, a crucial element in making individuals feel heard, while avoiding excessive practical suggestions, which may be less effective in achieving this goal. Our research underscores the potential…

Heterogeneous high-valent cobalt-oxo [≡Co(IV)=O] is a widely focused reactive species in oxidant activation; however, the relationship between the catalyst interfacial defects and ≡Co(IV)=O formation remains poorly understood. Herein, photoexcited oxygen vacancies (OVs) were introduced into Co 3 O 4 (OV-Co 3 O 4 ) by a UV-induced modification method to facilitate chlorite (ClO 2 – ) activation. Density functional theory calculations indicate that OVs result in low-coordinated Co atom, which can directionally anchor chlorite under the oxygen-atom trapping effect. Chlorite first undergoes homolytic O–Cl cleavage and transfers the dissociated O atom to the low-coordinated Co atom to form reactive ≡Co(IV)=O with a higher spin state. The reactive ≡Co(IV)=O rapidly extracts one electron from ClO 2 – to form chlorine dioxide (ClO 2 ), accompanied by the Co atom returning a lower spin state. As a result of the oxygen-atom trapping effect, the OV-Co 3 O 4 /chlorite system achieved a 3.5 times higher efficiency of sulfamethoxazole degradation (~0.1331 min −1 ) than the pristine Co 3 O 4…

The assumption that vegetation improves air quality is prevalent in scientific, popular, and political discourse. However, experimental and modeling studies show the effect of green space on air pollutant concentrations in urban settings is highly variable and context specific. We revisited the link between vegetation and air quality using satellite-derived changes of urban green space and air pollutant concentrations from 2,615 established monitoring stations over Europe and the United States. Between 2010 and 2019, stations recorded declines in ambient NO 2 , (particulate matter) PM 10 , and PM 2.5 (average of −3.14% y −1 ), but not O 3 (+0.5% y −1 ), pointing to the general success of recent policy interventions to restrict anthropogenic emissions. The effect size of total green space on air pollution was weak and highly variable, particularly at the street scale (15 to 60 m radius) where vegetation can restrict ventilation. However, when isolating changes in tree cover, we found a negative association with air pollution at borough to city scales (120 to 16,000 m) particularly…

Amino acid mutations that lower a protein's thermodynamic stability are implicated in numerous diseases, and engineered proteins with enhanced stability can be important in research and medicine. Computational methods for predicting how mutations perturb protein stability are, therefore, of great interest. Despite recent advancements in protein design using deep learning, in silico prediction of stability changes has remained challenging, in part due to a lack of large, high-quality training datasets for model development. Here, we describe ThermoMPNN, a deep neural network trained to predict stability changes for protein point mutations given an initial structure. In doing so, we demonstrate the utility of a recently released megascale stability dataset for training a robust stability model. We also employ transfer learning to leverage a second, larger dataset by using learned features extracted from ProteinMPNN, a deep neural network trained to predict a protein's amino acid sequence given its three-dimensional structure. We show that our method achieves state-of-the-art…

Climate change is increasing the frequency and severity of short-term (~1 y) drought events-the most common duration of drought-globally. Yet the impact of this intensification of drought on ecosystem functioning remains poorly resolved. This is due in part to the widely disparate approaches ecologists have employed to study drought, variation in the severity and duration of drought studied, and differences among ecosystems in vegetation, edaphic and climatic attributes that can mediate drought impacts. To overcome these problems and better identify the factors that modulate drought responses, we used a coordinated distributed experiment to quantify the impact of short-term drought on grassland and shrubland ecosystems. With a standardized approach, we imposed ~a single year of drought at 100 sites on six continents. Here we show that loss of a foundational ecosystem function-aboveground net primary production (ANPP)-was 60% greater at sites that experienced statistically extreme drought (1-in-100-y event) vs. those sites where drought was nominal (historically more common) in…

High-performance sodium storage at low temperature is urgent with the increasingly stringent demand for energy storage systems. However, the aggravated capacity loss is induced by the sluggish interfacial kinetics, which originates from the interfacial Na + desolvation. Herein, all-fluorinated anions with ultrahigh electron donicity, trifluoroacetate (TFA − ), are introduced into the diglyme (G2)-based electrolyte for the anion-reinforced solvates in a wide temperature range. The unique solvation structure with TFA − anions and decreased G2 molecules occupying the inner sheath accelerates desolvation of Na + to exhibit decreased desolvation energy from 4.16 to 3.49 kJ mol −1 and 24.74 to 16.55 kJ mol −1 beyond and below −20 °C, respectively, compared with that in 1.0 M NaPF 6 -G2. These enable the cell of Na||Na 3 V 2 (PO 4 ) 3 to deliver 60.2% of its room-temperature capacity and high capacity retention of 99.2% after 100 cycles at −40 °C. This work highlights regulation of solvation chemistry for highly stable sodium-ion batteries at low temperature.

The population loss of trained deep neural networks often follows precise power-law scaling relations with either the size of the training dataset or the number of parameters in the network. We propose a theory that explains the origins of and connects these scaling laws. We identify variance-limited and resolution-limited scaling behavior for both dataset and model size, for a total of four scaling regimes. The variance-limited scaling follows simply from the existence of a well-behaved infinite data or infinite width limit, while the resolution-limited regime can be explained by positing that models are effectively resolving a smooth data manifold. In the large width limit, this can be equivalently obtained from the spectrum of certain kernels, and we present evidence that large width and large dataset resolution-limited scaling exponents are related by a duality. We exhibit all four scaling regimes in the controlled setting of large random feature and pretrained models and test the predictions empirically on a range of standard architectures and datasets. We also observe several…

Soil organic carbon (SOC) is the largest carbon pool in terrestrial ecosystems and plays a crucial role in mitigating climate change and enhancing soil productivity. Microbial-derived carbon (MDC) is the main component of the persistent SOC pool. However, current formulas used to estimate the proportional contribution of MDC are plagued by uncertainties due to limited sample sizes and the neglect of bacterial group composition effects. Here, we compiled the comprehensive global dataset and employed machine learning approaches to refine our quantitative understanding of MDC contributions to total carbon storage. Our efforts resulted in a reduction in the relative standard errors in prevailing estimations by an average of 71% and minimized the effect of global variations in bacterial group compositions on estimating MDC. Our estimation indicates that MDC contributes approximately 758 Pg, representing approximately 40% of the global soil carbon stock. Our study updated the formulas of MDC estimation with improving the accuracy and preserving simplicity and practicality. Given the…

The present study examines the assumptions, modeling structure, and results of DICE-2023, the revised Dynamic Integrated Model of Climate and the Economy (DICE), updated to 2023. The revision contains major changes in the treatment of risk, the carbon and climate modules, the treatment of nonindustrial greenhouse gases, discount rates, as well as updates on all the major components. Noteworthy changes are a significant reduction in the target for the optimal (cost-beneficial) temperature path, a lower cost of reaching the 2 °C target, an analysis of the impact of the Paris Accord, and a major increase in the estimated social cost of carbon.

Ultraviolet radiation (UVR) is primarily recognized for its detrimental effects such as cancerogenesis, skin aging, eye damage, and autoimmune disorders. With exception of ultraviolet B (UVB) requirement in the production of vitamin D3, the positive role of UVR in modulation of homeostasis is underappreciated. Skin exposure to UVR triggers local responses secondary to the induction of chemical, hormonal, immune, and neural signals that are defined by the chromophores and extent of UVR penetration into skin compartments. These responses are not random and are coordinated by the cutaneous neuro-immuno-endocrine system, which counteracts the action of external stressors and accommodates local homeostasis to the changing environment. The UVR induces electrical, chemical, and biological signals to be sent to the brain, endocrine and immune systems, as well as other central organs, which in concert regulate body homeostasis. To achieve its central homeostatic goal, the UVR-induced signals are precisely computed locally with transmission through nerves or humoral signals release into the…

Oxygen evolution reaction (OER) is the pivotal obstacle of water splitting for hydrogen production. Dual-sites catalysts (DSCs) are considered exceeding single-site catalysts due to the preternatural synergetic effects of two metals in OER. However, appointing the specific spatial configuration of dual-sites toward more efficient catalysis still remains a challenge. Herein, we constructed two configurations of Fe-Co dual-sites: stereo Fe-Co sites (stereo-Fe-Co DSC) and planar Fe-Co sites (planar-Fe-Co DSC). Remarkably, the planar-Fe-Co DSC has excellent OER performance superior to stereo-Fe-Co DSC. DFT calculations and experiments including isotope differential electrochemical mass spectrometry, in situ infrared spectroscopy, and in situ Raman reveal the *O intermediates can be directly coupled to form *O-O* rather than *OOH by both the DSCs, which could overcome the limitation of four electron transfer steps in OER. Especially, the proper Fe-Co distance and steric direction of the planar-Fe-Co benefit the cooperation of dual sites to dehydrogenate intermediates into *O-O* than…

The Anthropocene signifies the start of a no-analogue trajectory of the Earth system that is fundamentally different from the Holocene. This new trajectory is characterized by rising risks of triggering irreversible and unmanageable shifts in Earth system functioning. We urgently need a new global approach to safeguard critical Earth system regulating functions more effectively and comprehensively. The global commons framework is the closest example of an existing approach with the aim of governing biophysical systems on Earth upon which the world collectively depends. Derived during stable Holocene conditions, the global commons framework must now evolve in the light of new Anthropocene dynamics. This requires a fundamental shift from a focus only on governing shared resources beyond national jurisdiction, to one that secures critical functions of the Earth system irrespective of national boundaries. We propose a new framework-the planetary commons-which differs from the global commons framework by including not only globally shared geographic regions but also critical biophysical…

Terrestrial enhanced weathering (EW) of silicate rocks, such as crushed basalt, on farmlands is a promising scalable atmospheric carbon dioxide removal (CDR) strategy that urgently requires performance assessment with commercial farming practices. We report findings from a large-scale replicated EW field trial across a typical maize-soybean rotation on an experimental farm in the heart of the United Sates Corn Belt over 4 y (2016 to 2020). We show an average combined loss of major cations (Ca 2+ and Mg 2+ ) from crushed basalt applied each fall over 4 y (50 t ha −1 y −1 ) gave a conservative time-integrated cumulative CDR potential of 10.5 ± 3.8 t CO 2 ha −1 . Maize and soybean yields increased significantly ( P < 0.05) by 12 to 16% with EW following improved soil fertility, decreased soil acidification, and upregulation of root nutrient transport genes. Yield enhancements with EW were achieved with significantly ( P < 0.05) increased key micro- and macronutrient concentrations (including potassium, magnesium, manganese, phosphorus, and zinc), thus improving or maintaining crop…

Direct use of metals as battery anodes could significantly boost the energy density, but suffers from limited cycling. To make the batteries more sustainable, one strategy is mitigating the propensity for metals to form random morphology during plating through orientation regulation, e.g., hexagonal Zn platelets locked horizontally by epitaxial electrodeposition or vertically aligned through Zn/electrolyte interface modulation. Current strategies center around obtaining (002) faceted deposition due to its minimum surface energy. Here, benefiting from the capability of preparing a library of faceted monocrystalline Zn anodes and controlling the orientation of Zn platelet deposits, we challenge this conventional belief. We show that while monocrystalline (002) faceted Zn electrode with horizontal epitaxy indeed promises the highest critical current density, the (100) faceted electrode with vertically aligned deposits is the most important one in suppressing Zn metal corrosion and promising the best reversibility. Such uniqueness results from the lowest electrochemical surface area of…

In our quest to leverage the capabilities of the emerging single-atom catalysts (SACs) for wastewater purification, we confronted fundamental challenges related to electron scarcity and instability. Through meticulous theoretical calculations, we identified optimal placements for nitrogen vacancies (Nv) and iron (Fe) single-atom sites, uncovering a dual-site approach that significantly amplified visible-light absorption and charge transfer dynamics. Informed by these computational insights, we cleverly integrated Nv into the catalyst design to boost electron density around iron atoms, yielding a potent and flexible photoactivator for benign peracetic acid. This exceptional catalyst exhibited remarkable stability and effectively degraded various organic contaminants over 20 cycles with self-cleaning properties. Specifically, the Nv sites captured electrons, enabling their swift transfer to adjacent Fe sites under visible light irradiation. This mechanism accelerated the reduction of the formed "peracetic acid-catalyst" intermediate. Theoretical calculations were used to elucidate the…

Lysine lactylation (Kla) is a new type of histone mark implicated in the regulation of various functional processes such as transcription. However, how this histone mark acts in cancers remains unexplored due in part to a lack of knowledge about its reader proteins. Here, we observe that cervical cancer (CC) cells undergo metabolic reprogram by which lactate accumulation and thereby boosts histone lactylation, particularly H3K14la. Utilizing a multivalent photoaffinity probe in combination with quantitative proteomics approach, we identify DPF2 as a candidate target of H3K14la. Biochemical studies as well as CUT&Tag analysis reveal that DPF2 is capable of binding to H3K14la and colocalizes with it on promoters of oncogenic genes. Notably, disrupting the DPF2-H3K14la interaction through structure-guided mutation blunts those cancer-related gene expression along with cell survival. Together, our findings reveal DPF2 as a bona fide H3K14la effector that couples histone lactylation to gene transcription and cell survival, offering insight into how histone Kla engages in transcription…

DNA structure can regulate genome function. Four-stranded DNA G-quadruplex (G4) structures have been implicated in transcriptional regulation; however, previous studies have not directly addressed the role of an individual G4 within its endogenous cellular context. Using CRISPR to genetically abrogate endogenous G4 structure folding, we directly interrogate the G4 found within the upstream regulatory region of the critical human MYC oncogene. G4 loss leads to suppression of MYC transcription from the P1 promoter that is mediated by the deposition of a de novo nucleosome alongside alterations in RNA polymerase recruitment. We also show that replacement of the endogenous MYC G4 with a different G4 structure from the KRAS oncogene restores G4 folding and MYC transcription. Moreover, we demonstrate that the MYC G4 structure itself, rather than its sequence, recruits transcription factors and histone modifiers. Overall, our work establishes that G4 structures are important features of transcriptional regulation that coordinate recruitment of key chromatin proteins and the transcriptional…

Sleep, circadian rhythms, and mental health are reciprocally interlinked. Disruption to the quality, continuity, and timing of sleep can precipitate or exacerbate psychiatric symptoms in susceptible individuals, while treatments that target sleep-circadian disturbances can alleviate psychopathology. Conversely, psychiatric symptoms can reciprocally exacerbate poor sleep and disrupt clock-controlled processes. Despite progress in elucidating underlying mechanisms, a cohesive approach that integrates the dynamic interactions between psychiatric disorder with both sleep and circadian processes is lacking. This review synthesizes recent evidence for sleep-circadian dysfunction as a transdiagnostic contributor to a range of psychiatric disorders, with an emphasis on biological mechanisms. We highlight observations from adolescent and young adults, who are at greatest risk of developing mental disorders, and for whom early detection and intervention promise the greatest benefit. In particular, we aim to a) integrate sleep and circadian factors implicated in the pathophysiology and…

While macrophage heterogeneity during metabolic dysfunction-associated steatohepatitis (MASH) has been described, the fate of these macrophages during MASH regression is poorly understood. Comparing macrophage heterogeneity during MASH progression vs regression, we identified specific macrophage subpopulations that are critical for MASH/fibrosis resolution. We elucidated the restorative pathways and gene signatures that define regression-associated macrophages and establish the importance of TREM2 + macrophages during MASH regression. Liver-resident Kupffer cells are lost during MASH and are replaced by four distinct monocyte-derived macrophage subpopulations. Trem2 is expressed in two macrophage subpopulations: i) monocyte-derived macrophages occupying the Kupffer cell niche (MoKC) and ii) lipid-associated macrophages (LAM). In regression livers, no new transcriptionally distinct macrophage subpopulation emerged. However, the relative macrophage composition changed during regression compared to MASH. While MoKC was the major macrophage subpopulation during MASH, they decreased…

Artificial neuromorphic devices can emulate dendric integration, axonal parallel transmission, along with superior energy efficiency in facilitating efficient information processing, offering enormous potential for wearable electronics. However, integrating such circuits into textiles to achieve biomimetic information perception, processing, and control motion feedback remains a formidable challenge. Here, we engineer a quasi-solid-state iontronic synapse fiber (ISF) comprising photoresponsive TiO 2 , ion storage Co-MoS 2 , and an ion transport layer. The resulting ISF achieves inherent short-term synaptic plasticity, femtojoule-range energy consumption, and the ability to transduce chemical/optical signals. Multiple ISFs are interwoven into a synthetic neural fabric, allowing the simultaneous propagation of distinct optical signals for transmitting parallel information. Importantly, IFSs with multiple input electrodes exhibit spatiotemporal information integration. As a proof of concept, a textile-based multiplexing neuromorphic sensorimotor system is constructed to connect…

Plants release a wealth of metabolites into the rhizosphere that can shape the composition and activity of microbial communities in response to environmental stress. The connection between rhizodeposition and rhizosphere microbiome succession has been suggested, particularly under environmental stress conditions, yet definitive evidence is scarce. In this study, we investigated the relationship between rhizosphere chemistry, microbiome dynamics, and abiotic stress in the bioenergy crop switchgrass grown in a marginal soil under nutrient-limited, moisture-limited, and nitrogen (N)-replete, phosphorus (P)-replete, and NP-replete conditions. We combined 16S rRNA amplicon sequencing and LC-MS/MS-based metabolomics to link rhizosphere microbial communities and metabolites. We identified significant changes in rhizosphere metabolite profiles in response to abiotic stress and linked them to changes in microbial communities using network analysis. N-limitation amplified the abundance of aromatic acids, pentoses, and their derivatives in the rhizosphere, and their enhanced availability was…

Creating efficient catalysts for simultaneous H 2 O 2 generation and pollutant degradation is vital. Piezocatalytic H 2 O 2 synthesis offers a promising alternative to traditional methods but faces challenges like sacrificial reagents, harsh conditions, and low activity. In this study, we introduce a cobalt-loaded ZnO (CZO) piezocatalyst that efficiently generates H 2 O 2 from H 2 O and O 2 under ultrasonic (US) treatment in ambient aqueous conditions. The catalyst demonstrates exceptional performance with ~50.9% TOC removal of phenol and in situ generation of 1.3 mM H 2 O 2 , significantly outperforming pure ZnO. Notably, the CZO piezocatalyst maintains its H 2 O 2 generation capability even after multiple cycles, showing continuous improvement (from 1.3 mM to 1.8 mM). This is attributed to the piezoelectric electrons promoting the generation of dynamic defects under US conditions, which in turn promotes the adsorption and activation of oxygen, thereby facilitating efficient H 2 O 2 production, as confirmed by EPR spectrometry, XPS analysis, and DFT calculations. Moreover, the CZO…

Protein language models (pLMs) have emerged as potent tools for predicting and designing protein structure and function, and the degree to which these models fundamentally understand the inherent biophysics of protein structure stands as an open question. Motivated by a discovery that pLM-based structure predictors erroneously predict nonphysical structures for protein isoforms, we investigated the nature of sequence context needed for contact predictions in the pLM ESM-2. We demonstrate by use of a “categorical Jacobian” calculation that ESM-2 stores statistics of coevolving residues, analogously to simpler modelling approaches like Markov Random Fields and Multivariate Gaussian models. We further investigated how ESM-2 “stores” information needed to predict contacts by comparing sequence masking strategies, and found that providing local windows of sequence information allowed ESM-2 to best recover predicted contacts. This suggests that pLMs predict contacts by storing motifs of pairwise contacts. Our investigation highlights the limitations of current pLMs and underscores the…

Ferroptosis is an iron-dependent type of regulated cell death resulting from extensive lipid peroxidation and plays a critical role in various physiological and pathological processes. However, the regulatory mechanisms for ferroptosis sensitivity remain incompletely understood. Here, we report that homozygous deletion of Usp8 (ubiquitin-specific protease 8) in intestinal epithelial cells (IECs) leads to architectural changes in the colonic epithelium and shortens mouse lifespan accompanied by increased IEC death and signs of lipid peroxidation. However, mice with heterozygous deletion of Usp8 in IECs display normal phenotype and become resistant to azoxymethane/dextran sodium sulfate–induced colorectal tumorigenesis. Mechanistically, USP8 interacts with and deubiquitinates glutathione peroxidase 4 (GPX4), leading to GPX4 stabilization. Thus, USP8 inhibition destabilizes GPX4 and sensitizes cancer cells to ferroptosis in vitro. Notably, USP8 inhibition in combination with ferroptosis inducers retards tumor growth and enhances CD8 + T cell infiltration, which potentiates tumor…

Effectively managing sewage sludge from Fenton reactions in an eco-friendly way is vital for Fenton technology’s viability in pollution treatment. This study focuses on sewage sludge across various treatment stages, including generation, concentration, dehydration, and landfill, and employs chemical composite MoS 2 to facilitate green resource utilization of all types of sludge. MoS 2 , with exposed Mo 4+ and low-coordination sulfur, enhances iron cycling and creates an acidic microenvironment on the sludge surface. The MoS 2 -modified iron sludge exhibits outstanding (>95%) phenol and pollutant degradation in hydrogen peroxide and peroxymonosulfate-based Fenton systems, unlike unmodified sludge. This modified sludge maintains excellent Fenton activity in various water conditions and with multiple anions, allowing extended phenol degradation for over 14 d. Notably, the generated chemical oxygen demand (COD) in sludge modification process can be efficiently eliminated through the Fenton reaction, ensuring effluent COD compliance and enabling eco-friendly sewage sludge resource…

Understanding the molecular-level mechanisms involved in transmembrane ion selectivity is essential for optimizing membrane separation performance. In this study, we reveal our observations regarding the transmembrane behavior of Li + and Mg 2+ ions as a response to the changing pore solvation abilities of the covalent-organic-framework (COF) membranes. These abilities were manipulated by adjusting the lengths of the oligoether segments attached to the pore channels. Through comparative experiments, we were able to unravel the relationships between pore solvation ability and various ion transport properties, such as partitioning, conduction, and selectivity. We also emphasize the significance of the competition between Li + and Mg 2+ with the solvating segments in modulating selectivity. We found that increasing the length of the oligoether chain facilitated ion transport; however, it was the COF membrane with oligoether chains containing two ethylene oxide units that exhibited the most pronounced discrepancy in transmembrane energy barrier between Li + and Mg 2+ , resulting in the…

The brain's remarkable and efficient information processing capability is driving research into brain-inspired (neuromorphic) computing paradigms. Artificial aqueous ion channels are emerging as an exciting platform for neuromorphic computing, representing a departure from conventional solid-state devices by directly mimicking the brain's fluidic ion transport. Supported by a quantitative theoretical model, we present easy-to-fabricate tapered microchannels that embed a conducting network of fluidic nanochannels between a colloidal structure. Due to transient salt concentration polarization, our devices are volatile memristors (memory resistors) that are remarkably stable. The voltage-driven net salt flux and accumulation, that underpin the concentration polarization, surprisingly combine into a diffusionlike quadratic dependence of the memory retention time on the channel length, allowing channel design for a specific timescale. We implement our device as a synaptic element for neuromorphic reservoir computing. Individual channels distinguish various time series, that together…

Recently, there has been a notable surge in interest regarding reclaiming valuable chemicals from waste plastics. However, the energy-intensive conventional thermal catalysis does not align with the concept of sustainable development. Herein, we report a sustainable electrocatalytic approach allowing the selective synthesis of glycolic acid (GA) from waste polyethylene terephthalate (PET) over a Pd 67 Ag 33 alloy catalyst under ambient conditions. Notably, Pd 67 Ag 33 delivers a high mass activity of 9.7 A mg Pd −1 for ethylene glycol oxidation reaction (EGOR) and GA Faradaic efficiency of 92.7 %, representing the most active catalyst for selective GA synthesis. In situ experiments and computational simulations uncover that ligand effect induced by Ag incorporation enhances the GA selectivity by facilitating carbonyl intermediates desorption, while the lattice mismatch-triggered tensile strain optimizes the adsorption of *OH species to boost reaction kinetics. This work unveils the synergistic of strain and ligand effect in alloy catalyst and provides guidance for the design of…

During real-time language comprehension, our minds rapidly decode complex meanings from sequences of words. The difficulty of doing so is known to be related to words' contextual predictability, but what cognitive processes do these predictability effects reflect? In one view, predictability effects reflect facilitation due to anticipatory processing of words that are predictable from context. This view predicts a linear effect of predictability on processing demand. In another view, predictability effects reflect the costs of probabilistic inference over sentence interpretations. This view predicts either a logarithmic or a superlogarithmic effect of predictability on processing demand, depending on whether it assumes pressures toward a uniform distribution of information over time. The empirical record is currently mixed. Here, we revisit this question at scale: We analyze six reading datasets, estimate next-word probabilities with diverse statistical language models, and model reading times using recent advances in nonlinear regression. Results support a logarithmic effect of…

Electrochemical ammonia (NH 3 ) synthesis from nitrate reduction (NITRR) offers an appealing solution for addressing environmental concerns and the energy crisis. However, most of the developed electrocatalysts reduce NO 3 − to NH 3 via a hydrogen (H*)-mediated reduction mechanism, which suffers from undesired H*-H* dimerization to H 2 , resulting in unsatisfactory NH 3 yields. Herein, we demonstrate that reversed I 1 Cu 4 single-atom sites, prepared by anchoring iodine single atoms on the Cu surface, realized superior NITRR with a superior ammonia yield rate of 4.36 mg h −1 cm −2 and a Faradaic efficiency of 98.5% under neutral conditions via a proton-coupled electron transfer (PCET) mechanism, far beyond those of traditional Cu sites (NH 3 yield rate of 0.082 mg h −1 cm −2 and Faradaic efficiency of 36.5%) and most of H*-mediated NITRR electrocatalysts. Theoretical calculations revealed that I single atoms can regulate the local electronic structures of adjacent Cu sites in favor of stronger O-end-bidentate NO 3 − adsorption with dual electron transfer channels and suppress the H*…

Modeling complex physical dynamics is a fundamental task in science and engineering. Traditional physics-based models are first-principled, explainable, and sample-efficient. However, they often rely on strong modeling assumptions and expensive numerical integration, requiring significant computational resources and domain expertise. While deep learning (DL) provides efficient alternatives for modeling complex dynamics, they require a large amount of labeled training data. Furthermore, its predictions may disobey the governing physical laws and are difficult to interpret. Physics-guided DL aims to integrate first-principled physical knowledge into data-driven methods. It has the best of both worlds and is well equipped to better solve scientific problems. Recently, this field has gained great progress and has drawn considerable interest across discipline Here, we introduce the framework of physics-guided DL with a special emphasis on learning dynamical systems. We describe the learning pipeline and categorize state-of-the-art methods under this framework. We also offer our…

Deforestation poses a global threat to biodiversity and its capacity to deliver ecosystem services. Yet, the impacts of deforestation on soil biodiversity and its associated ecosystem services remain virtually unknown. We generated a global dataset including 696 paired-site observations to investigate how native forest conversion to other land uses affects soil properties, biodiversity, and functions associated with the delivery of multiple ecosystem services. The conversion of native forests to plantations, grasslands, and croplands resulted in higher bacterial diversity and more homogeneous fungal communities dominated by pathogens and with a lower abundance of symbionts. Such conversions also resulted in significant reductions in carbon storage, nutrient cycling, and soil functional rates related to organic matter decomposition. Responses of the microbial community to deforestation, including bacterial and fungal diversity and fungal guilds, were predominantly regulated by changes in soil pH and total phosphorus. Moreover, we found that soil fungal diversity and functioning in…

Nonradicals are effective in selectively degrading electron-rich organic contaminants, which unfortunately suffer from unsatisfactory yield and uncontrollable composition due to the competitive generation of radicals. Herein, we precisely construct a local microenvironment of the carbon nitride–supported high-loading (~9 wt.%) Fe single-atom catalyst (Fe SAC) with sulfur via a facile supermolecular self-assembly strategy. Short-distance S coordination boosts the peroxymonosulfate (PMS) activation and selectively generates high-valent iron–oxo species (Fe IV =O) along with singlet oxygen ( 1 O 2 ), significantly increasing the 1 O 2 yield, PMS utilization, and p -chlorophenol reactivity by 6.0, 3.0, and 8.4 times, respectively. The composition of nonradicals is controllable by simply changing the S content. In contrast, long-distance S coordination generates both radicals and nonradicals, and could not promote reactivity. Experimental and theoretical analyses suggest that the short-distance S upshifts the d -band center of the Fe atom, i.e., being close to the Fermi level, which…

A high-fat diet (HFD) is a high-risk factor for the malignant progression of cancers through the disruption of the intestinal microbiota. However, the role of the HFD-related gut microbiota in cancer development remains unclear. This study found that obesity and obesity-related gut microbiota were associated with poor prognosis and advanced clinicopathological status in female patients with breast cancer. To investigate the impact of HFD-associated gut microbiota on cancer progression, we established various models, including HFD feeding, fecal microbiota transplantation, antibiotic feeding, and bacterial gavage, in tumor-bearing mice. HFD-related microbiota promotes cancer progression by generating polymorphonuclear myeloid-derived suppressor cells (PMN-MDSCs). Mechanistically, the HFD microbiota released abundant leucine, which activated the mTORC1 signaling pathway in myeloid progenitors for PMN-MDSC differentiation. Clinically, the elevated leucine level in the peripheral blood induced by the HFD microbiota was correlated with abundant tumoral PMN-MDSC infiltration and poor…

California, a pioneer in EV adoption, has enacted ambitious electric vehicle (EV) policies that will generate a large burden on the state's electric distribution system. We investigate the statewide impact of uncontrolled EV charging on the electric distribution networks at a large scale and high granularity, by employing an EV charging profile projection that combines travel demand model, EV adoption model, and real-world EV charging data. We find a substantial need for infrastructure upgrades in 50% of feeders by 2035, and 67% of feeders by 2045. The distribution system across California must upgrade its capacity by 25 GW by 2045, corresponding to a cost between $6 and $20 billion. While the additional infrastructure cost drives the electricity price up, it is offset by the downward pressure from the growth of total electricity consumption and leads to a reduction in electricity rate between $0.01 and $0.06/kWh by 2045. We also find that overloading conditions are highly diverse spatially, with feeders in residential areas requiring twice as much upgrade compared to commercial…

Recent advancements in large language models (LLMs) have raised the prospect of scalable, automated, and fine-grained political microtargeting on a scale previously unseen; however, the persuasive influence of microtargeting with LLMs remains unclear. Here, we build a custom web application capable of integrating self-reported demographic and political data into GPT-4 prompts in real-time, facilitating the live creation of unique messages tailored to persuade individual users on four political issues. We then deploy this application in a pre-registered randomized control experiment (n = 8,587) to investigate the extent to which access to individual-level data increases the persuasive influence of GPT-4. Our approach yields two key findings. First, messages generated by GPT-4 were broadly persuasive, in some cases increasing levels of support for an issue stance by nearly 50%. Second, in aggregate, the persuasive impact of microtargeted messages was not statistically different from that of non-microtargeted messages (5.68% vs 7.32%, respec- tively, P = 0.082). These trends hold even…

The broad and substantial educational harm caused by the COVID-19 pandemic has motivated large federal, state, and local investments in academic recovery. However, the success of these efforts depends in part on students' regular school attendance. Using state-level data, I show that the rate of chronic absenteeism among US public-school students grew substantially as students returned to in-person instruction. Specifically, between the 2018-2019 and 2021-2022 school years, the share of students chronically absent grew by 13.5 percentage points-a 91-percent increase that implies an additional 6.5 million students are now chronically absent. State-level increases in chronic absenteeism are positively associated with the prevalence of school closures during the 2020-2021 school year. However, these increases do not appear to be associated with enrollment loss, COVID-19 case rates, school masking policies, or declines in youth mental health. This evidence indicates that the barriers to learning implied by the sharp increase in chronic absenteeism merit further scrutiny and policy…

Despite a sea of interpretability methods that can produce plausible explanations, the field has also empirically seen many failure cases of such methods. In light of these results, it remains unclear for practitioners how to use these methods and choose between them in a principled way. In this paper, we show that for moderately rich model classes (easily satisfied by neural networks), any feature attribution method that is complete and linear-for example, Integrated Gradients and Shapley Additive Explanations (SHAP)-can provably fail to improve on random guessing for inferring model behavior. Our results apply to common end-tasks such as characterizing local model behavior, identifying spurious features, and algorithmic recourse. One takeaway from our work is the importance of concretely defining end-tasks: Once such an end-task is defined, a simple and direct approach of repeated model evaluations can outperform many other complex feature attribution methods.

Abstract Despite the substantial evidence on the health effects of short-term exposure to ambient fine particles (PM 2.5 ), including increasing studies focusing on those from wildland fire smoke, the impacts of long-term wildland fire smoke PM 2.5 exposure remain unclear. We investigated the association between long-term exposure to wildland fire smoke PM 2.5 and non-accidental mortality and mortality from a wide range of specific causes in all 3,108 counties in the contiguous U.S., 2007–2020. Controlling for non-smoke PM 2.5 , air temperature, and unmeasured spatial and temporal confounders, we found a non-linear association between 12-month moving average concentration of smoke PM 2.5 and monthly non-accidental mortality rate. Relative to a month with the long-term smoke PM 2.5 exposure below 0.1 μg/m 3 , non-accidental mortality increased by 0.16-0.63 and 2.11 deaths per 100,000 people per month when the 12-month moving average of PM 2.5 concentration was of 0.1-5 and 5+ μg/m 3 , respectively. Cardiovascular, ischemic heart disease, digestive, endocrine, diabetes, mental, and…

Soil moisture (SM) is essential for sustaining services from Earth’s critical zone, a thin-living skin spanning from the canopy to groundwater. In the Anthropocene epoch, intensive afforestation has remarkably contributed to global greening and certain service improvements, often at the cost of reduced SM. However, attributing the response of SM in deep soil to such human activities is a great challenge because of the scarcity of long-term observations. Here, we present a 37 y (1985 to 2021) analysis of SM dynamics at two scales across China’s monsoon loess critical zone. Site-scale data indicate that land-use conversion from arable cropland to forest/grassland caused an 18% increase in SM deficit over 0 to 18 m depth ( P < 0.01). Importantly, this SM deficit intensified over time, despite limited climate change influence. Across the Loess Plateau, SM storage in 0 to 10 m layer exhibited a significant decreasing trend from 1985 to 2021, with a turning point in 1999 when starting afforestation. Compared with SM storage before 1999, the relative contributions of climate change and…

We study the adoption of ChatGPT, the icon of Generative AI, using a large-scale survey linked to comprehensive register data in Denmark. Surveying 18,000 workers from 11 exposed occupations, we document that ChatGPT is widespread, especially among younger and less-experienced workers. However, substantial inequalities have emerged. Women are 16 percentage points less likely to have used the tool for work. Furthermore, despite its potential to lift workers with less expertise, users of ChatGPT earned slightly more already before its arrival, even given their lower tenure. Workers see a substantial productivity potential in ChatGPT but are often hindered by employer restrictions and a perceived need for training.

Fluoro-substitution solvents have achieved great success in electrolyte engineering for high-energy lithium metal batteries, which, however, is beset by low solvating power, thermal and chemical instability, and possible battery swelling. Instead, we herein introduce cyanogen as the electron-withdrawing group to enhance the oxidative stability of ether solvents, in which cyanogen and ether oxygen form the chelating structure with Li + not notably undermining the solvating power. Cyano-group strongly bonds with transition metals (TMs) of NCM811 cathode to attenuate the catalytic reactivity of TMs toward bulk electrolytes. Besides, a stable and uniform cathode–electrolyte interphase (CEI) inhibits the violent oxidation decomposition of electrolytes and guarantees the structural integrity of the NCM811 cathode. Also, a N-containing and LiF-rich solid–electrolyte interphase (SEI) in our electrolyte facilitates fast Li + migration and dense Li deposition. Accordingly, our electrolyte enables a stable cycle of Li metal anode with Coulombic efficiency of 98.4% within 100 cycles. 81.8%…

Reduction of carbon dioxide (CO 2 ) by renewable electricity to produce multicarbon chemicals, such as ethylene (C 2 H 4 ), continues to be a challenge because of insufficient Faradaic efficiency, low production rates, and complex mechanistic pathways. Here, we report that the rate-determining steps (RDS) on common copper (Cu) surfaces diverge in CO 2 electroreduction, leading to distinct catalytic performances. Through a combination of experimental and computational studies, we reveal that C─C bond-making is the RDS on Cu(100), whereas the protonation of *CO with adsorbed water becomes rate-limiting on Cu(111) with a higher energy barrier. On an oxide-derived Cu(100)-dominant Cu catalyst, we reach a high C 2 H 4 Faradaic efficiency of 72%, partial current density of 359 mA cm −2 , and long-term stability exceeding 100 h at 500 mA cm −2 , greatly outperforming its Cu(111)-rich counterpart. We further demonstrate constant C 2 H 4 selectivity of >60% over 70 h in a membrane electrode assembly electrolyzer with a full-cell energy efficiency of 23.4%.

Nanoparticle-based RNA delivery has shown great progress in recent years with the approval of two mRNA vaccines for Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) and a liver-targeted siRNA therapy. Here, we discuss the preclinical and clinical advancement of new generations of RNA delivery therapies along multiple axes. Improvements in cargo design such as RNA circularization and data-driven untranslated region optimization can drive better mRNA expression. New materials discovery research has driven improved delivery to extrahepatic targets such as the lung and splenic immune cells, which could lead to pulmonary gene therapy and better cancer vaccines, respectively. Other organs and even specific cell types can be targeted for delivery via conjugation of small molecule ligands, antibodies, or peptides to RNA delivery nanoparticles. Moreover, the immune response to any RNA delivery nanoparticle plays a crucial role in determining efficacy. Targeting increased immunogenicity without induction of reactogenic side effects is crucial for vaccines, while minimization of…

Singlet oxygen ( 1 O 2 ) is important in the environmental remediation field, however, its efficient production has been severely hindered by the ultrafast self-quenching of the as-generated radical precursors in the Fenton-like reactions. Herein, we elaborately designed lamellar anthraquinone-based covalent organic frameworks (DAQ-COF) with sequential localization of the active sites (C═O) at molecular levels for visible-light-assisted peroxymonosulfate (PMS) activation. Theoretical and experimental results revealed that the radical precursors (SO 5 ·− ) were formed in the nearby layers with the migration distance less than 0.34 nm, via PMS donating electrons to the photogenerated holes. This interlayer synergistic effect eventually led to ultraefficient 1 O 2 production (14.8 μM s −1 ), which is 12 times that of the highest reported catalyst. As an outcome, DAQ-COF enabled the complete degradation of bisphenol A in 5 min with PMS under natural sunlight irradiation. This interlayer synergistic concept represents an innovative and effective strategy to increase the utilization…

Microplastic is globally regarded as an important factor impacting biogeochemical cycles, yet our understanding of such influences is limited by the uncertainties of intricate microbial processes. By multiomics analysis, coupled with soil chemodiversity characterization and microbial carbon use efficiency (CUE), we investigated how microbial responses to microplastics impacted soil carbon cycling in a long-term field experiment. We showed that biodegradable microplastics promoted soil organic carbon accrual by an average of 2.47%, while nondegradable microplastics inhibited it by 17.4%, as a consequence of the virus–bacteria coadaptations to the microplastics disturbance. In the relevant functional pathways, nondegradable microplastics significantly ( P < 0.05) enhanced the abundance and transcriptional activity related to complex carbohydrate metabolism, whereas biodegradable microplastics significantly ( P < 0.05) promoted functions involved in amino acid metabolism and glycolysis. Accordingly, viral lysis enhanced in nondegradable microplastics treatments to introduce more…

Interactions mediated by intrinsically disordered protein regions (IDRs) pose formidable challenges in structural characterization. IDRs are highly versatile, capable of adopting diverse structures and engagement modes. Motivated by recent strides in protein structure prediction, we embarked on exploring the extent to which AlphaFold-Multimer can faithfully reproduce the intricacies of interactions involving IDRs. To this end, we gathered multiple datasets covering the versatile spectrum of IDR binding modes and used them to probe AlphaFold-Multimer's prediction of IDR interactions and their dynamics. Our analyses revealed that AlphaFold-Multimer is not only capable of predicting various types of bound IDR structures with high success rate, but that distinguishing true interactions from decoys, and unreliable predictions from accurate ones is achievable by appropriate use of AlphaFold-Multimer's intrinsic scores. We found that the quality of predictions drops for more heterogeneous, fuzzy interaction types, most likely due to lower interface hydrophobicity and higher coil content.…

It is imperative to devise effective removal strategies for high ionization potential (IP) organic pollutants in wastewater as their reduced electron-donating capacity challenges the efficiency of advanced oxidation systems in degradation. Against this backdrop, leveraging the metal-based carbon material structure meticulously, we employed metal-pyridine-N (M-N-C, M=Fe, Co, and Ni) as the electron transfer bridge. This distinctive design facilitated the ordered transfer of electrons from the adsorbent surface to the surface of high IP value pollutants, acting as a "supplement" to compensate for their deficient electron-donating capability, thereby culminating in the selective adsorption of these pollutants. Furthermore, this adsorbent also demonstrated effective removal of trace emerging contaminants (2 mg/L), displayed robust resistance to various salts, exhibited reusability, and maintained stability. These findings carry substantial implications for future carbon-based material design, offering a pathway toward exceptional adsorption performance in treating water pollution.

High-entropy alloy nanoparticles (HEANs) possessing regulated defect structure and electron interaction exhibit a guideline for constructing multifunctional catalysts. However, the microstructure-activity relationship between active sites of HEANs for multifunctional electrocatalysts is rarely reported. In this work, HEANs distributed on multi-walled carbon nanotubes (HEAN/CNT) are prepared by Joule heating as an example to explain the mechanism of trifunctional electrocatalysis for oxygen reduction, oxygen evolution, and hydrogen evolution reaction. HEAN/CNT excels with unmatched stability, maintaining a 0.8V voltage window for 220 h in zinc-air batteries. Even after 20 h of water electrolysis, its performance remains undiminished, highlighting exceptional endurance and reliability. Moreover, the intrinsic characteristics of the defect structure and electron interaction for HEAN/CNT are investigated in detail. The electrocatalytic mechanism of trifunctional electrocatalysis of HEAN/CNT under different conditions is identified by in situ monitoring and theoretical calculation.…

Large language models (LLMs) are currently at the forefront of intertwining AI systems with human communication and everyday life. Thus, aligning them with human values is of great importance. However, given the steady increase in reasoning abilities, future LLMs are under suspicion of becoming able to deceive human operators and utilizing this ability to bypass monitoring efforts. As a prerequisite to this, LLMs need to possess a conceptual understanding of deception strategies. This study reveals that such strategies emerged in state-of-the-art LLMs, but were nonexistent in earlier LLMs. We conduct a series of experiments showing that state-of-the-art LLMs are able to understand and induce false beliefs in other agents, that their performance in complex deception scenarios can be amplified utilizing chain-of-thought reasoning, and that eliciting Machiavellianism in LLMs can trigger misaligned deceptive behavior. GPT-4, for instance, exhibits deceptive behavior in simple test scenarios 99.16% of the time ( P < 0.001). In complex second-order deception test scenarios where the aim…

The widespread adoption of large language models (LLMs) makes it important to recognize their strengths and limitations. We argue that to develop a holistic understanding of these systems, we must consider the problem that they were trained to solve: next-word prediction over Internet text. By recognizing the pressures that this task exerts, we can make predictions about the strategies that LLMs will adopt, allowing us to reason about when they will succeed or fail. Using this approach-which we call the teleological approach-we identify three factors that we hypothesize will influence LLM accuracy: the probability of the task to be performed, the probability of the target output, and the probability of the provided input. To test our predictions, we evaluate five LLMs (GPT-3.5, GPT-4, Claude 3, Llama 3, and Gemini 1.0) on 11 tasks, and we find robust evidence that LLMs are influenced by probability in the hypothesized ways. Many of the experiments reveal surprising failure modes. For instance, GPT-4's accuracy at decoding a simple cipher is 51% when the output is a high-probability…

Lithium is an emerging strategic resource for modern energy transformation toward electrification and decarbonization. However, current mainstream direct lithium extraction technology via adsorption suffers from sluggish kinetics and intensive water usage, especially in arid/semiarid and cold salt-lake regions (natural land brines). Herein, an efficient proof-of-concept integrated solar microevaporator system is developed to realize synergetic solar-enhanced lithium recovery and water footprint management from hypersaline salt-lake brines. The 98% solar energy harvesting efficiency of the solar microevaporator system, elevating its local temperature, greatly promotes the endothermic Li + extraction process and solar steam generation. Benefiting from the photothermal effect, enhanced water flux, and enriched local Li + supply in nanoconfined space, a double-enhanced Li + recovery capacity was delivered (increase from 12.4 to 28.7 mg g −1 ) under one sun, and adsorption kinetics rate (saturated within 6 h) also reached twice of that at 280 K (salt-lake temperature). Additionally, the…

Soil organic carbon (SOC) is vital for terrestrial ecosystems, affecting biogeochemical processes, and soil health. It is known that soil salinity impacts SOC content, yet the specific direction and magnitude of SOC variability in relation to soil salinity remain poorly understood. Analyzing 43,459 mineral soil samples (SOC < 150 g kg −1 ) collected across different land covers since 1992, we approximate a soil salinity increase from 1 to 5 dS m −1 in croplands would be associated with a decline in mineral soils SOC from 0.14 g kg −1 above the mean predicted SOC ( SOC ¯ c = 18.47 g kg −1 ) to 0.46 g kg −1 below SOC ¯ c (~−430%), while for noncroplands, such decline is sharper, from 0.96 above SOC ¯ nc = 35.96 g kg −1 to 4.99 below SOC ¯ nc (~−620%). Although salinity’s significance in explaining SOC variability is minor (<6%), we estimate a one SD increase in salinity of topsoil samples (0 to 7 cm) correlates with respective SOC ¯ declines of ~4.4% and ~9.26%, relative to SOC ¯ c and SOC ¯ nc . The SOC ¯ decline in croplands is greatest in vegetation/cropland mosaics while lands…

We synthesized ammonia (NH 3 ) by bubbling nitrogen (N 2 ) gas into bulk liquid water (200 mL) containing 50 mg polytetrafluoroethylene (PTFE) particles (~5 µm in diameter) suspended with the help of a surfactant (Tween 20, ~0.05 vol.%) at room temperature (25 °C). Electron spin resonance spectroscopy and density functional theory calculations reveal that water acts as the proton donor for the reduction of N 2 . Moreover, isotopic labeling of the N 2 gas shows that it is the source of nitrogen in the ammonia. We propose a mechanism for ammonia generation based on the activation of N 2 caused by electron transfer and reduction processes driven by contact electrification. We optimized the pH of the PTFE suspension at 6.5 to 7.0 and employed ultrasonic mixing. We found an ammonia production rate of ~420 μmol L −1 h −1 per gram of PTFE particles for the conditions described above. This rate did not change more than 10% over an 8-h period of sustained reaction.

As bees' main source of protein and lipids, pollen is critical for their development, reproduction, and health. Plant species vary considerably in the macronutrient content of their pollen, and research in bee model systems has established that this variation both modulates performance and guides floral choice. Yet, how variation in pollen chemistry shapes interactions between plants and bees in natural communities is an open question, essential for both understanding the nutritional dynamics of plant-pollinator mutualisms and informing their conservation. To fill this gap, we asked how pollen nutrition (relative protein and lipid content) sampled from 109 co-flowering plant species structured visitation patterns observed among 75 subgenera of pollen-collecting bees in the Great Basin/Eastern Sierra region (USA). We found that the degree of similarity in co-flowering plant species' pollen nutrition predicted similarity among their visitor communities, even after accounting for floral morphology and phylogeny. Consideration of pollen nutrition also shed light on the structure of this…

CO 2 mineralization products are often heralded as having outstanding potentials to reduce CO 2 -eq. emissions. However, these claims are generally undermined by incomplete consideration of the life cycle climate change impacts, material properties, supply and demand constraints, and economic viability of CO 2 mineralization products. We investigate these factors in detail for ten concrete-related CO 2 mineralization products to quantify their individual and global CO 2 -eq. emissions reduction potentials. Our results show that in 2020, 3.9 Gt of carbonatable solid materials were generated globally, with the dominant material being end-of-life cement paste in concrete and mortar (1.4 Gt y –1 ). All ten of the CO 2 mineralization technologies investigated here reduce life cycle CO 2 -eq. emissions when used to substitute comparable conventional products. In 2020, the global CO 2 -eq. emissions reduction potential of economically competitive CO 2 mineralization technologies was 0.39 Gt CO 2 -eq., i.e., 15% of that from cement production. This level of CO 2 -eq. emissions reduction is…

Proteins mediate their functions through chemical interactions; modeling these interactions, which are typically through sidechains, is an important need in protein design. However, constructing an all-atom generative model requires an appropriate scheme for managing the jointly continuous and discrete nature of proteins encoded in the structure and sequence. We describe an all-atom diffusion model of protein structure, Protpardelle, which instantiates a "superposition" over the possible sidechain states, and collapses it to conduct reverse diffusion for sample generation. When combined with sequence design methods, our model is able to co-design all-atom protein structure and sequence. Generated proteins are of good quality under the typical quality, diversity, and novelty metrics, and sidechains reproduce the chemical features and behavior of natural proteins. Finally, we explore the potential of our model conduct all-atom protein design and scaffold functional motifs in a backbone- and rotamer-free way.

We study the effect of Facebook and Instagram access on political beliefs, attitudes, and behavior by randomizing a subset of 19,857 Facebook users and 15,585 Instagram users to deactivate their accounts for 6 wk before the 2020 U.S. election. We report four key findings. First, both Facebook and Instagram deactivation reduced an index of political participation (driven mainly by reduced participation online). Second, Facebook deactivation had no significant effect on an index of knowledge, but secondary analyses suggest that it reduced knowledge of general news while possibly also decreasing belief in misinformation circulating online. Third, Facebook deactivation may have reduced self-reported net votes for Trump, though this effect does not meet our preregistered significance threshold. Finally, the effects of both Facebook and Instagram deactivation on affective and issue polarization, perceived legitimacy of the election, candidate favorability, and voter turnout were all precisely estimated and close to zero.

Single-atom catalysts (SACs) with atomic dispersion active sites have exhibited huge potentials in peroxymonosulfate (PMS)-based Fenton-like chemistry in water purification. However, four-N coordination metal (MN 4 ) moieties often suffer from such problems as low selectivity and narrow workable pH. How to construct SACs in a controllable strategy with optimized electronic structures is of great challenge. Herein, an innovative strategy (i.e., the “4 + 1” fabrication) was devised to precisely modulate the first-shell coordinated microenvironment of FeN 4 SAC using an additional N (SA-FeN 5 ). This leads to almost 100% selective formation of high-valent iron-oxo [Fe(IV)═O] (steady-state concentration: 2.00 × 10 −8 M) in the SA-FeN 5 /PMS system. In-depth theoretical calculations unveil that FeN 5 configuration optimizes the electron distribution of monatomic Fe sites, which thus fosters PMS adsorption and reduces the energy barrier for Fe(IV)═O generation. SA-FeN 5 was then attached to polyvinylidene difluoride membrane for a continuous flow device, showing long-term abatement of the…

While aqueous zinc-ion batteries exhibit great potential, their performance is impeded by zinc dendrites. Existing literature has proposed the use of hydrogel electrolytes to ameliorate this issue. Nevertheless, the mechanical attributes of hydrogel electrolytes, particularly their modulus, are suboptimal, primarily ascribed to the substantial water content. This drawback would severely restrict the dendrite-inhibiting efficacy, especially under large mass loadings of active materials. Inspired by the structural characteristics of wood, this study endeavors to fabricate the anisotropic carboxymethyl cellulose hydrogel electrolyte through directional freezing, salting-out effect, and compression reinforcement, aiming to maximize the modulus along the direction perpendicular to the electrode surface. The heightened modulus concurrently serves to suppress the vertical deposition of the intermediate product at the cathode. Meanwhile, the oriented channels with low tortuosity enabled by the anisotropic structure are beneficial to the ionic transport between the anode and cathode.…

Nearly five billion people use and receive news through social media and there is widespread concern about the negative consequences of misinformation on social media (e.g., election interference, vaccine hesitancy). Despite a burgeoning body of research on misinformation, it remains largely unclear who is susceptible to misinformation and why. To address this, we conducted a systematic individual participant data meta-analysis covering 256,337 unique choices made by 11,561 US-based participants across 31 experiments. Our meta-analysis reveals the impact of key demographic and psychological factors on online misinformation veracity judgments. We also disentangle the ability to discern between true and false news (discrimination ability) from response bias, that is, the tendency to label news as either true (true-news bias) or false (false-news bias). Across all studies, participants were well above-chance accurate for both true (68.51%) and false (67.24%) news headlines. We find that older age, higher analytical thinking skills, and identifying as a Democrat are associated with…

The brain is composed of complex networks of interacting neurons that express considerable heterogeneity in their physiology and spiking characteristics. How does this neural heterogeneity influence macroscopic neural dynamics, and how might it contribute to neural computation? In this work, we use a mean-field model to investigate computation in heterogeneous neural networks, by studying how the heterogeneity of cell spiking thresholds affects three key computational functions of a neural population: the gating, encoding, and decoding of neural signals. Our results suggest that heterogeneity serves different computational functions in different cell types. In inhibitory interneurons, varying the degree of spike threshold heterogeneity allows them to gate the propagation of neural signals in a reciprocally coupled excitatory population. Whereas homogeneous interneurons impose synchronized dynamics that narrow the dynamic repertoire of the excitatory neurons, heterogeneous interneurons act as an inhibitory offset while preserving excitatory neuron function. Spike threshold…

The Asian water tower (AWT) serves as the source of 10 major Asian river systems and supports the lives of ~2 billion people. Obtaining reliable precipitation data over the AWT is a prerequisite for understanding the water cycle within this pivotal region. Here, we quantitatively reveal that the "observed" precipitation over the AWT is considerably underestimated in view of observational evidence from three water cycle components, namely, evapotranspiration, runoff, and accumulated snow. We found that three paradoxes appear if the so-called observed precipitation is corrected, namely, actual evapotranspiration exceeding precipitation, unrealistically high runoff coefficients, and accumulated snow water equivalent exceeding contemporaneous precipitation. We then explain the cause of precipitation underestimation from instrumental error caused by wind-induced gauge undercatch and the representativeness error caused by sparse-uneven gauge density and the complexity of local surface conditions. These findings require us to rethink previous results concerning the water cycle, prompting…

Organic carbon availability in soil is crucial for shaping microbial communities, yet, uncertainties persist concerning microbial adaptations to carbon levels and the ensuing ecological and evolutionary consequences. We investigated organic carbon metabolism, antibiotic resistance, and virus-host interactions in soils subjected to 40 y of chemical and organic fertilization that led to contrasting carbon availability: carbon-poor and carbon-rich soils, respectively. Carbon-poor soils drove the enrichment of putative genes involved in organic matter decomposition and exhibited specialization in utilizing complex organic compounds, reflecting scramble competition. This specialization confers a competitive advantage of microbial communities in carbon-poor soils but reduces their buffering capacity in terms of organic carbon metabolisms, making them more vulnerable to environmental fluctuations. Additionally, in carbon-poor soils, viral auxiliary metabolic genes linked to organic carbon metabolism increased host competitiveness and environmental adaptability through a strategy akin to…

Urbanization has accelerated dramatically across the world over the past decades. Urban influence on surface temperatures is now being considered as a correction term in climatological datasets. Although prior research has investigated urban influences on precipitation for specific cities or selected thunderstorm cases, a comprehensive examination of urban precipitation anomalies on a global scale remains limited. This research is a global analysis of urban precipitation anomalies for over one thousand cities worldwide. We find that more than 60% of the global cities and their downwind regions are receiving more precipitation than the surrounding rural areas. Moreover, the magnitude of these urban wet islands has nearly doubled in the past 20 y. Urban precipitation anomalies exhibit variations across different continents and climates, with cities in Africa, for example, exhibiting the largest urban annual and extreme precipitation anomalies. Cities are more prone to substantial urban precipitation anomalies under warm and humid climates compared to cold and dry climates. Cities with…

Peroxymonosulfate-based electrochemical advanced oxidation processes (PMS-EAOPs) have great potential for sustainable water purification, so an in-depth understanding of its catalytic mechanism is imperative to facilitate its practical application. Herein, the performance enhancement and mechanism of electroenhanced PMS activation by single-atom Fe catalyst modified carbon felt was investigated. Compared with the anode, the cathode exhibited faster bisphenol A degradation ( k cathode = 0.073 vs. k anode = 0.015 min −1 ), increased PMS consumption (98.8 vs. 10.3%), and an order of magnitude reduction of Fe dissolution (0.068 vs. 0.787 mg L −1 ). Mass transfer is a key factor limiting PMS activation, while the electrostriction of water in the hydrophobic region caused by cathode electric field (CEF) significantly increased mass transfer coefficient ( k m, cathode = 1.49 × 10 −4 vs. k m, anode = 2.68 × 10 −5 m s −1 ). The enhanced activation of PMS is a synergistic result between electroactivation and catalyst-activation, which is controlled by the applied current density. 1 O 2 and…

In the pursuit of mental and physical health, effective pain management stands as a cornerstone. Here, we examine a potential sex bias in pain management. Leveraging insights from psychological research showing that females' pain is stereotypically judged as less intense than males' pain, we hypothesize that there may be tangible differences in pain management decisions based on patients' sex. Our investigation spans emergency department (ED) datasets from two countries, including discharge notes of patients arriving with pain complaints (N = 21,851). Across these datasets, a consistent sex disparity emerges. Female patients are less likely to be prescribed pain-relief medications compared to males, and this disparity persists even after adjusting for patients' reported pain scores and numerous patient, physician, and ED variables. This disparity extends across medical practitioners, with both male and female physicians prescribing less pain-relief medications to females than to males. Additional analyses reveal that female patients' pain scores are 10% less likely to be recorded by…

Proteomics has been revolutionized by large protein language models (PLMs), which learn unsupervised representations from large corpora of sequences. These models are typically fine-tuned in a supervised setting to adapt the model to specific downstream tasks. However, the computational and memory footprint of fine-tuning (FT) large PLMs presents a barrier for many research groups with limited computational resources. Natural language processing has seen a similar explosion in the size of models, where these challenges have been addressed by methods for parameter-efficient fine-tuning (PEFT). In this work, we introduce this paradigm to proteomics through leveraging the parameter-efficient method LoRA and training new models for two important tasks: predicting protein-protein interactions (PPIs) and predicting the symmetry of homooligomer quaternary structures. We show that these approaches are competitive with traditional FT while requiring reduced memory and substantially fewer parameters. We additionally show that for the PPI prediction task, training only the classification head…

Atomically dispersed catalysts are a promising alternative to platinum group metal catalysts for catalyzing the oxygen reduction reaction (ORR), while limited durability during the electrocatalytic process severely restricts their practical application. Here, we report an atomically dispersed Co-doped carbon−nitrogen bilayer catalyst with unique dual-axial Co–C bonds (denoted as Co/DACN) by a smart phenyl-carbon-induced strategy, realizing highly efficient electrocatalytic ORR in both alkaline and acidic media. The corresponding half-wave potential for ORR is up to 0.85 and 0.77 V (vs. reversible hydrogen electrode (RHE)) in 0.5 M H 2 SO 4 and 0.1 M KOH, respectively, representing the best ORR activity among all non-noble metal catalysts reported to date. Impressively, the Zn–air battery (ZAB) equipped with Co/DACN cathode achieves outstanding durability after 1,688 h operation at 10 mA cm −2 with a high current density (154.2 mA cm −2 ) and a peak power density (210.1 mW cm −2 ). Density functional theory calculations reveal that the unique dual-axial cross-linking Co−C bonds of…

The pathological deposition of proteins is a hallmark of several devastating neurodegenerative diseases. These pathological deposits comprise aggregates of proteins that adopt distinct structures named strains. However, the molecular factors responsible for the formation of distinct aggregate strains are unknown. Here, we show that the serine/threonine kinase GSK3β catalyzes the aggregation of the protein tau into Alzheimer's disease (AD)-like filaments. We demonstrate that phosphorylation by GSK3β, but not by several other kinases, promotes the aggregation of full-length tau as well as enhances phase separation into gel-like condensate structures. Cryoelectron microscopy further reveals that the fibrils formed by GSK3β-phosphorylated tau adopt a fold comparable to that of paired helical filaments isolated from the brains of AD patients. Our results elucidate the intricate relationship between posttranslational modification and the formation of tau strains in neurodegenerative diseases.

Immune-mediated necrotizing myopathy (IMNM) is an autoimmune disorder associated with the presence of autoantibodies, characterized by severe clinical presentation with rapidly progressive muscular weakness and elevated levels of creatine kinase, while traditional pharmacological approaches possess varying and often limited effects. Considering the pathogenic role of autoantibodies, chimeric antigen receptor (CAR)-T cells targeting B cell maturation antigen (BCMA) have emerged as a promising therapeutic strategy. We reported here a patient with anti-signal recognition particle IMNM refractory to multiple available therapies, who was treated with BCMA-targeting CAR-T cells, exhibited favorable safety profiles, sustained reduction in pathogenic autoantibodies, and persistent clinical improvements over 18 mo. Longitudinal single-cell RNA, B cell receptor, T cell receptor sequencing analysis presented the normalization of immune microenvironment after CAR-T cell infusion, including reconstitution of B cell lineages, replacement of T cell subclusters, and suppression of overactivated…

Wildfires have become more frequent and intense due to climate change and outdoor wildfire fine particulate matter (PM 2.5 ) concentrations differ from relatively smoothly varying total PM 2.5 . Thus, we introduced a conceptual model for computing long-term wildfire PM 2.5 and assessed disproportionate exposures among marginalized communities. We used monitoring data and statistical techniques to characterize annual wildfire PM 2.5 exposure based on intermittent and extreme daily wildfire PM 2.5 concentrations in California census tracts (2006 to 2020). Metrics included: 1) weeks with wildfire PM 2.5 > 5 μg/m 3 ; 2) days with non-zero wildfire PM 2.5 ; 3) mean wildfire PM 2.5 during peak exposure week; 4) smoke waves (≥2 consecutive days with >15 μg/m 3 wildfire PM 2.5 ); and 5) mean annual wildfire PM 2.5 concentration. We classified tracts by their racial/ethnic composition and CalEnviroScreen (CES) score, an environmental and social vulnerability composite measure. We examined associations of CES and racial/ethnic composition with the wildfire PM 2.5 metrics using mixed-effects…

Surface roughness ubiquitously prevails in natural faults across various length scales. Despite extensive studies highlighting the important role of fault geometry in the dynamics of tectonic earthquakes, whether and how fault roughness affects fluid-induced seismicity remains elusive. Here, we investigate the effects of fault geometry and stress heterogeneity on fluid-induced fault slip and associated seismicity characteristics using laboratory experiments and numerical modeling. We perform fluid injection experiments on quartz-rich sandstone samples containing either a smooth or a rough fault. We find that geometrical roughness slows down injection-induced fault slip and reduces macroscopic slip velocities and fault slip-weakening rates. Stress heterogeneity and roughness control hypocenter distribution, frequency–magnitude characteristics, and source mechanisms of injection-induced acoustic emissions (AEs) (analogous to natural seismicity). In contrast to smooth faults where injection-induced AEs are uniformly distributed, slip on rough faults produces spatially localized AEs…

The electro-Fenton process is a state-of-the-art water treatment technology used to remove organic contaminants. However, the low O 2 utilization efficiency (OUE, <1%) and high energy consumption remain the biggest obstacles to practical application. Here, we propose a local O 2 concentrating (LOC) approach to increase the OUE by over 11-fold compared to the conventional simple O 2 diffusion route. Due to the well-designed molecular structure, the LOC approach enables direct extraction of O 2 from the bulk solution to the reaction interface; this eliminates the need to pump O 2 /air to overcome the sluggish O 2 mass transfer and results in high Faradaic efficiencies (~50%) even under natural air diffusion conditions. Long-term operation of a flow-through pilot device indicated that the LOC approach saved more than 65% of the electric energy normally consumed in treating actual industrial wastewater, demonstrating the great potential of this system-level design to boost the electro-Fenton process for energy-efficient water remediation.

Metal-organic frameworks (MOFs) are superior ion adsorbents for selectively capturing toxic ions from water. Nevertheless, they have rarely been reported to have lithium selectivity over divalent cations due to the well-known flexibility of MOF framework and the similar physiochemical properties of Li + and Mg 2+ . Herein, we report an ion-sieving adsorption approach to design sunlight-regenerable lithium adsorbents by subnanoporous MOFs for efficient lithium extraction. By integrating the ion-sieving agent of MOFs with light-responsive adsorption sites of polyspiropyran (PSP), the ion-sieving adsorption behaviors of PSP-MOFs with 6.0, 8.5, and 10.0 Å windows are inversely proportional to their pore size. The synthesized PSP-UiO-66 with a narrowest window size of 6.0 Å shows high LiCl adsorption capacity up to 10.17 mmol g −1 and good Li + /Mg 2+ selectivity of 5.8 to 29 in synthetic brines with Mg/Li ratio of 1 to 0.1. It could be quickly regenerated by sunlight irradiation in 6 min with excellent cycling performance of 99% after five cycles. This work sheds light on designing…

Self-organized spatial patterns are a common feature of complex systems, ranging from microbial communities to mussel beds and drylands. While the theoretical implications of these patterns for ecosystem-level processes, such as functioning and resilience, have been extensively studied, empirical evidence remains scarce. To address this gap, we analyzed global drylands along an aridity gradient using remote sensing, field data, and modeling. We found that the spatial structure of the vegetation strengthens as aridity increases, which is associated with the maintenance of a high level of soil multifunctionality, even as aridity levels rise up to a certain threshold. The combination of these results with those of two individual-based models indicate that self-organized vegetation patterns not only form in response to stressful environmental conditions but also provide drylands with the ability to adapt to changing conditions while maintaining their functioning, an adaptive capacity which is lost in degraded ecosystems. Self-organization thereby plays a vital role in enhancing the…

Periodic spin-orbit motion is ubiquitous in nature, observed from electrons orbiting nuclei to spinning planets orbiting the Sun. Achieving autonomous periodic orbiting motions, along circular and noncircular paths, in soft mobile robotics is crucial for adaptive and intelligent exploration of unknown environments-a grand challenge yet to be accomplished. Here, we report leveraging a closed-loop twisted ring topology with a defect for an autonomous soft robot capable of achieving periodic spin-orbiting motions with programmed circular and re-programmed irregular-shaped trajectories. Constructed by bonding a twisted liquid crystal elastomer ribbon into a closed-loop ring topology, the robot exhibits three coupled periodic self-motions in response to constant temperature or constant light sources: inside-out flipping, self-spinning around the ring center, and self-orbiting around a point outside the ring. The coupled spinning and orbiting motions share the same direction and period. The spinning or orbiting direction depends on the twisting chirality, while the orbital radius and…

Rechargeable zinc–air batteries (ZABs) are regarded as a remarkably promising alternative to current lithium-ion batteries, addressing the requirements for large-scale high-energy storage. Nevertheless, the sluggish kinetics involving oxygen reduction reaction (ORR) and oxygen evolution reaction (OER) hamper the widespread application of ZABs, necessitating the development of high-efficiency and durable bifunctional electrocatalysts. Here, we report oxygen atom–bridged Fe, Co dual-metal dimers (FeOCo-SAD), in which the active site Fe–O–Co–N 6 moiety boosts exceptional reversible activity toward ORR and OER in alkaline electrolytes. Specifically, FeOCo-SAD achieves a half-wave potential ( E 1/2 ) of 0.87 V for ORR and an overpotential of 310 mV at a current density of 10 mA cm –2 for OER, with a potential gap (Δ E ) of only 0.67 V. Meanwhile, FeOCo-SAD manifests high performance with a peak power density of 241.24 mW cm −2 in realistic rechargeable ZABs. Theoretical calculations demonstrate that the introduction of an oxygen bridge in the Fe, Co dimer induced charge spatial…

The photocatalytic CO 2 -to-CH 4 conversion involves multiple consecutive proton–electron coupling transfer processes. Achieving high CH 4 selectivity with satisfactory conversion efficiency remains challenging since the inefficient proton and electron delivery path results in sluggish proton–electron transfer kinetics. Herein, we propose the fabrication of atomically adjacent anion–cation vacancy as paired redox active sites that could maximally promote the proton- and electron-donating efficiency to simultaneously enhance the oxidation and reduction half-reactions, achieving higher photocatalytic CO 2 reduction activity and CH 4 selectivity. Taking TiO 2 as a photocatalyst prototype, the operando electron paramagnetic resonance spectra, quasi in situ X-ray photoelectron spectroscopy measurements, and high-angle annular dark-field-scanning transmission electron microscopy image analysis prove that the V Ti on TiO 2 as initial sites can induce electron redistribution and facilitate the escape of the adjacent oxygen atom, thereby triggering the dynamic creation of atomically adjacent…

Adding a cationic helper lipid to a lipid nanoparticle (LNP) can increase lung delivery and decrease liver delivery. However, it remains unclear whether charge-dependent tropism is universal or, alternatively, whether it depends on the component that is charged. Here, we report evidence that cationic cholesterol-dependent tropism can differ from cationic helper lipid-dependent tropism. By testing how 196 LNPs delivered mRNA to 22 cell types, we found that charged cholesterols led to a different lung:liver delivery ratio than charged helper lipids. We also found that combining cationic cholesterol with a cationic helper lipid led to mRNA delivery in the heart as well as several lung cell types, including stem cell-like populations. These data highlight the utility of exploring charge-dependent LNP tropism.

We investigate the moiré band structures and the strong correlation effects in twisted bilayer MoTe[Formula: see text] for a wide range of twist angles, employing a combination of various techniques. Using large-scale first-principles calculations, we pinpoint realistic continuum modeling parameters, subsequently deriving the maximally localized Wannier functions for the top three moiré bands. Simplifying our model with reasonable assumptions, we obtain a minimal two-band model, encompassing Coulomb repulsion, correlated hopping, and spin exchange. Our minimal interaction models pave the way for further exploration of the rich many-body physics in twisted MoTe[Formula: see text]. Furthermore, we explore the phase diagrams of the system through Hartree-Fock approximation and exact diagonalization (ED). Our two-band ED analysis underscores significant band-mixing effects in this system, which enlarge the optimal twist angle for fractional quantum anomalous Hall states.

Fibroblast growth factor receptor (FGFR) kinase inhibitors have been shown to be effective in the treatment of intrahepatic cholangiocarcinoma and other advanced solid tumors harboring FGFR2 alterations, but the toxicity of these drugs frequently leads to dose reduction or interruption of treatment such that maximum efficacy cannot be achieved. The most common adverse effects are hyperphosphatemia caused by FGFR1 inhibition and diarrhea due to FGFR4 inhibition, as current therapies are not selective among the FGFRs. Designing selective inhibitors has proved difficult with conventional approaches because the orthosteric sites of FGFR family members are observed to be highly similar in X-ray structures. In this study, aided by analysis of protein dynamics, we designed a selective, covalent FGFR2 inhibitor. In a key initial step, analysis of long-timescale molecular dynamics simulations of the FGFR1 and FGFR2 kinase domains allowed us to identify differential motion in their P-loops, which are located adjacent to the orthosteric site. Using this insight, we were able to design…

Abstract Many prokaryotic and eukaryotic cells metabolize glucose to organism-specific byproducts instead of fully oxidizing it to carbon dioxide and water–a phenomenon referred to as the Warburg Effect. The benefit to a cell has been unclear, given that partial metabolism of glucose yields an order of magnitude less ATP per molecule of glucose than complete oxidation. We show that glycolysis produces ATP faster per gram of pathway protein than respiration in E. coli , S. cerevisiae , and mammalian cells. A simple mathematical model that uses yield, rate, and proteome occupancy of glycolysis and respiration as the only parameters accurately predicts absolute rates of glycolysis and respiration in all three organisms under diverse conditions. Our study suggests that the Warburg Effect is a consequence of the optimization of the rate of energy generation under the constraint of finite proteome space. One-Sentence Summary The Warburg Effect is a manifestation by which cells across kingdoms of life optimize the rate of energy production.

The recent theory-driven discovery of a class of clathrate hydrides (e.g., CaH 6 , YH 6 , YH 9 , and LaH 10 ) with superconducting critical temperatures ( T c ) well above 200 K has opened the prospects for “hot” superconductivity above room temperature under pressure. Recent efforts focus on the search for superconductors among ternary hydrides that accommodate more diverse material types and configurations compared to binary hydrides. Through extensive computational searches, we report the prediction of a unique class of thermodynamically stable clathrate hydrides structures consisting of two previously unreported H 24 and H 30 hydrogen clathrate cages at megabar pressures. Among these phases, LaSc 2 H 24 shows potential hot superconductivity at the thermodynamically stable pressure range of 167 to 300 GPa, with calculated T c s up to 331 K at 250 GPa and 316 K at 167 GPa when the important effects of anharmonicity are included. The very high critical temperatures are attributed to an unusually large hydrogen-derived density of states at the Fermi level arising from the newly…

The observed rate of global warming since the 1970s has been proposed as a strong constraint on equilibrium climate sensitivity (ECS) and transient climate response (TCR)-key metrics of the global climate response to greenhouse-gas forcing. Using CMIP5/6 models, we show that the inter-model relationship between warming and these climate sensitivity metrics (the basis for the constraint) arises from a similarity in transient and equilibrium warming patterns within the models, producing an effective climate sensitivity (EffCS) governing recent warming that is comparable to the value of ECS governing long-term warming under CO[Formula: see text] forcing. However, CMIP5/6 historical simulations do not reproduce observed warming patterns. When driven by observed patterns, even high ECS models produce low EffCS values consistent with the observed global warming rate. The inability of CMIP5/6 models to reproduce observed warming patterns thus results in a bias in the modeled relationship between recent global warming and climate sensitivity. Correcting for this bias means that observed…

Cell-type-specific in vivo delivery of genome editing molecules is the next breakthrough that will drive biological discovery and transform the field of cell and gene therapy. Here, we discuss recent advances in the delivery of CRISPR-Cas genome editors either as preassembled ribonucleoproteins or encoded in mRNA. Both strategies avoid pitfalls of viral vector-mediated delivery and offer advantages including transient editor lifetime and potentially streamlined manufacturing capability that are already proving valuable for clinical use. We review current applications and future opportunities of these emerging delivery approaches that could make genome editing more efficacious and accessible in the future.

Music is powerful in conveying emotions and triggering affective brain mechanisms. Affective brain responses in previous studies were however rather inconsistent, potentially because of the non-adaptive nature of recorded music used so far. Live music instead can be dynamic and adaptive and is often modulated in response to audience feedback to maximize emotional responses in listeners. Here, we introduce a setup for studying emotional responses to live music in a closed-loop neurofeedback setup. This setup linked live performances by musicians to neural processing in listeners, with listeners' amygdala activity was displayed to musicians in real time. Brain activity was measured using functional MRI, and especially amygdala activity was quantified in real time for the neurofeedback signal. Live pleasant and unpleasant piano music performed in response to amygdala neurofeedback from listeners was acoustically very different from comparable recorded music and elicited significantly higher and more consistent amygdala activity. Higher activity was also found in a broader neural…

MXenes have demonstrated potential for various applications owing to their tunable surface chemistry and metallic conductivity. However, high temperatures can accelerate MXene film oxidation in air. Understanding the mechanisms of MXene oxidation at elevated temperatures, which is still limited, is critical in improving their thermal stability for high-temperature applications. Here, we demonstrate that Ti[Formula: see text]C[Formula: see text]T[Formula: see text] MXene monoflakes have exceptional thermal stability at temperatures up to 600[Formula: see text]C in air, while multiflakes readily oxidize in air at 300[Formula: see text]C. Density functional theory calculations indicate that confined water between Ti[Formula: see text]C[Formula: see text]T[Formula: see text] flakes has higher removal energy than surface water and can thus persist to higher temperatures, leading to oxidation. We demonstrate that the amount of confined water correlates with the degree of oxidation in stacked flakes. Confined water can be fully removed by vacuum annealing Ti[Formula: see text]C[Formula:…

Treatment with autologous chimeric antigen receptor (CAR) T cells has emerged as a highly effective approach in neuroimmunological disorders such as myasthenia gravis. We report a case of successful anti-CD19 CAR T cell use in treatment-refractory stiff-person syndrome (SPS). To investigate clinical and immunological effects of anti-CD19 CAR T cell use in treatment-refractory SPS, a 69-y-old female with a 9-y history of treatment-refractory SPS with deteriorating episodes of stiffness received an infusion of autologous anti-CD19 CAR T cells (KYV-101) and was monitored clinically and immunologically for more than 6 mo. CAR T cell infusion resulted in reduced leg stiffness, drastic improvement in gait, walking speed increase over 100%, and daily walking distance improvement from less than 50 m to over 6 km within 3 mo. GABAergic medication (benzodiazepines) was reduced by 40%. KYV-101 CAR T cells were well tolerated with only low-grade cytokine release syndrome. This report of successful use of anti-CD19 CAR T cells in treatment-refractory SPS supports continued exploration of this…

The prion-like spread of protein aggregates is a leading hypothesis for the propagation of neurofibrillary lesions in the brain, including the spread of tau inclusions associated with Alzheimer's disease. The mechanisms of cellular uptake of tau seeds and subsequent nucleated polymerization of cytosolic tau are major questions in the field, and the potential for coupling between the entry and nucleation mechanisms has been little explored. We found that in primary astrocytes, endocytosis of tau seeds leads to their accumulation in lysosomes. This in turn leads to lysosomal swelling, deacidification and recruitment of ESCRT proteins, but not Galectin-3, to the lysosomal membrane. These observations are consistent with nanoscale damage of the lysosomal membrane. Using live cell and STORM, imaging, nucleation of cytosolic tau occurs primarily at the lysosome membrane under these conditions. These data suggest that tau seeds escape from lysosomes via nanoscale damage rather than wholesale rupture, and that nucleation of cytosolic tau commences as soon as tau fibril ends emerge from the…

Abstract We developed a significantly improved genetically encoded quantitative adenosine triphosphate (ATP) sensor to provide real-time dynamics of ATP levels in subcellular compartments. iATPSnFR2 is a variant of iATPSnFR1, a previously developed sensor that has circularly permuted super-folder GFP inserted between the ATP-binding helices of the ε -subunit of a bacterial F 0 -F 1 ATPase. Optimizing the linkers joining the two domains resulted in a ∼ 5-6 fold improvement in the dynamic range compared to the previous generation sensor, with excellent discrimination against other analytes and affinity variants varying from 4 μM to 500 μM. A chimeric version of this sensor fused to either the HaloTag protein or a suitably spectrally separated fluorescent protein, provides a ratiometric readout allowing comparisons of ATP across cellular regions. Subcellular targeting of the sensor to nerve terminals reveals previously uncharacterized single synapse metabolic signatures, while targeting to the mitochondrial matrix allowed direct quantitative probing of oxidative phosphorylation…