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Marine heatwaves shift ocean net primary productivity from the tropics toward the poles
Abstract Marine heatwaves (MHWs), prolonged extreme thermal events, are reshaping ocean ecosystems, yet their influence on global productivity patterns remains poorly understood. Here, we use a global regression framework to disentangle linear thermal effect from nonlinear feedback and demonstrate that MHWs restructure the dominant drivers of ocean net primary production (NPP). MHWs induce a regime shift from sea surface temperature (SST)-independent to SST-dependent controls on NPP anomaly, reflecting an enhanced thermal effect in response to extreme warming. MHW suppressed the NPP anomaly across nutrient-poor low latitudes but increased it in nutrient-rich higher latitudes. The contrasting responses arise from differences in nutrient baselines, with low-nutrient regions exhibiting greater sensitivity to extreme warming. Together, these results reveal an emerging poleward redistribution of ocean productivity and highlight the need to incorporate MHWs into projections of marine ecosystem resilience and climate–biosphere feedbacks.
Homoharringtonine exhibits senotherapeutic activity that mitigates diet- and age-associated obesity and insulin resistance and extends lifespan in mice
Abstract The accumulation of senescent cells in white adipose tissue (WAT) is closely associated with the functional decline of WAT and plays a causal role in the pathogenesis of metabolic diseases. Therefore, the elimination of senescent cells in WAT holds promise for the treatment and prevention of age-related metabolic diseases. Using a drug-repositioning strategy for 2150 clinically applied compounds, we discover that homoharringtonine (HHT), an FDA-approved anti-leukemic drug, manifests senotherapeutic activity in vitro in multiple cell types including human preadipocytes, while inflicting minimal cytotoxicity to non-senescent cells. HHT treatment prevents diet- or age-induced metabolic abnormalities in male mice targeting senescent adipocytes and preadipocytes to improve WAT function and reduce WAT inflammation. Moreover, HHT treatment attenuates age-associated phenotypes of human adipose tissue. Mechanistically, the senotherapeutic effects of HHT are mediated through the direct interaction of HHT with heat shock protein family A member 5 (HSPA5). Importantly, we found that HHT treatment delays aging and extends the lifespan in progeroid and aged mice. Our study demonstrates the novel senotherapeutic potential of HHT to mitigate age- and obesity-related metabolic dysfunction and extend longevity in mice.
Pathogenic KIF1A R350 mutations disrupt a conserved and conformation-dependent kinesin-tubulin salt bridge
Concurrent chemoradiotherapy plus nimotuzumab versus chemoradiotherapy alone for locoregionally advanced nasopharyngeal carcinoma with a suboptimal response to induction chemotherapy: a randomized phase 2 trial
Identification of a universal three-body s-wave resonance in 10He
Single-molecule neuromorphic device with aJ-level power consumption per switching
Pulmonary fibroblast activation during Aspergillus fumigatus infection enhances lung defense via immunomodulation and tissue remodeling
Trisomy 21 Drives ADARB1 Overexpression and Premature RNA Recoding in the Developing Fetal Brain
Reversible phase-transformation-induced thermal quenching in Mn(II) chlorides for high-precision information encryption and thermal energy storage
Simultaneous profiling of native-state proteomes and transcriptomes of neural cell types using proximity labeling
Nucleophagy is promoted by two autophagy receptors and inhibited by chromatin-nuclear envelope tethering in fission yeast
Abstract Selective autophagy of the nucleus, known as nucleophagy, targets nuclear components for degradation. The molecular mechanisms underlying nucleophagy remain inadequately understood. In this study, we identify a nucleophagy receptor, Npr1, in the fission yeast Schizosaccharomyces pombe . Npr1 is an Atg8-binding multi-transmembrane protein localized to the outer nuclear membrane. It functions redundantly with another autophagy receptor, Epr1, to promote nitrogen starvation-induced nucleophagy. In the absence of both Npr1 and Epr1, starved cells exhibit abnormal nuclear morphology and reduced survival. During nucleophagy, the nuclear envelope (NE) forms outward protrusions where Atg8 co-localizes with Npr1 and/or Epr1. These protrusions subsequently detach from the NE, resulting in the formation of autophagosomes that contain nucleophagy cargo. Notably, artificially enhancing chromatin association with the inner nuclear membrane leads to NE protrusions that fail to detach, thereby aborting nucleophagy. Our findings provide mechanistic insights into nucleophagy and suggest that abortive nucleophagy protects chromatin from degradation.
Correction for Lee et al., Emergence of a contrast-invariant representation of naturalistic texture in macaque visual cortex
Physics-constrained neural ordinary differential equation models to discover and predict microbial community dynamics
Microbial communities play essential roles in shaping ecosystem functions and predictive modeling frameworks are crucial for understanding, controlling, and harnessing their properties. Competition and cross-feeding of metabolites drives microbiome dynamics and functions. Existing mechanistic models that capture metabolite-mediated interactions in microbial communities have limited flexibility due to rigid assumptions. While machine learning models provide flexibility, they require large datasets, are challenging to interpret, and can overfit to experimental noise. To overcome these limitations, we develop a physics-constrained machine learning model, which we call the neural species mediator (NSM), that combines a mechanistic model of metabolite dynamics with a machine learning component. The NSM outperforms mechanistic or machine learning components on in vitro experimental datasets and provides insights into direct biological interactions. In summary, carefully embedding a neural network into a mechanistic model of microbial community dynamics improves prediction performance and interpretability compared to its constituent mechanistic or machine learning components.
One test, many tongues: Surveying language proficiency across the globe
Language influences our thinking and affects many aspects of cognition, from how we perceive the world to how we interact socially. Thus, objectively characterizing linguistic background is crucial for research in many areas, including second language acquisition, psycho-linguistics, and cognitive science. Traditional language proficiency tests, however, are manually composed by experts, limiting their scope for both lab and online settings. Here, we propose a pipeline that automatically derives a language proficiency test from a corpus of text and applies it to create new tests for 1,939 languages. Using this approach, we conducted a large-scale survey examining L1 and L2 proficiency across 34 countries, with participants tested on all 34 languages. Drawing from human ratings from 4,137 participants, our results validate that our test can effectively distinguish native speakers, second-language speakers, and nonspeakers within one minute, making it an effective tool for evaluating linguistic proficiency. We show that participants’ linguistic and demographic backgrounds systematically influence both their language proficiency and their self-reported skills, and we map the prevalence of global languages, such as English and Spanish, among online participants. Moreover, we show that our vocabulary tests are strongly correlated with other linguistic competences—such as listening and writing—in a set of typologically varied languages, demonstrating our test is an efficient instrument to assess language proficiency. More broadly, our work offers a significant resource for investigating global variation in language skills and contributes to reducing the overreliance on the English language in the cognitive and social sciences.
Versatile artificial muscles by decoupling anisotropy
Artificial muscles offer unique advantages for robotics, but their inability to adapt to diverse scenarios significantly limits their widespread application. We present the helical anisotropically reinforced polymer actuator (HARP)—a versatile class of artificial muscles. The HARP not only exhibits state-of-the-art performance (contraction ratios up to 75%, power densities of 1.93 kW/kg, and energy efficiencies of 29%) but also possesses a broad and decoupled design space, i.e., the anisotropy source, tube, and core can be independently and freely selected. This decoupled design space enables the selection of numerous useful properties (e.g., abrasion resistance, high specific work, etc.). Using this, we demonstrate that the HARP can satisfy the requirements of diverse applications by tuning the selection of parameters. This is especially important for applications necessitating multiple requirements simultaneously, like a maneuverable continuum robot or an untethered musculoskeletal quadruped. Unifying high performance with versatility within a single artificial muscle framework, the HARP offers a practical path toward deploying artificial muscles across a wide spectrum of robotic systems.
Correction for Ranjan et al., The E3 ubiquitin ligase RNF186 and <i>RNF186</i> risk variants regulate innate receptor-induced outcomes
Dynamical modeling of individual sensory reactivity and habituation learning
Empirical research on sensory processing often focuses on group averages to uncover how sensory input translates into behavior. While this population-level approach has revealed important general principles of genetic and environmental control of behavior, it masks the rich and potentially meaningful variation observed at the level of individuals. Key features of sensory processing are reactivity, the degree to which a stimulus elicits a response, and habituation, a fundamental learning process that serves as a cognitive filter by reducing the response to repeated, irrelevant stimuli. We developed a model-based approach to quantify individual sensory processing dynamics, using a visual escape paradigm in Drosophila . We collected light-off jump responses in more than two hundred flies and quantified them individually via Bayesian inference of a dynamical model’s parameters. Considering both reactivity and habituation, we found that quantitative properties of individual responses vary greatly even in an isogenic population raised under identical environmental conditions. By moving from population averages to individual-based analyses, we uncover and quantify pronounced stochasticity in individual responses. Furthermore, we found that individual reactivity and habituation parameters display substantial temporal stability over a two-week interval, indicating that these behaviors are stable, intrinsic properties of an individual. The presented framework enables robust stratification of individual behavioral phenotypes and provides a quantitative platform for modeling interindividual differences in sensory processing, including frequently observed atypical responses in neurogenetic diseases.
Small-molecule CBLB inhibitor abolishes EGFR ubiquitination, reduces receptor endocytosis, and diminishes cell motility signaling
Endocytosis of the epidermal growth factor receptor (EGFR) is considered a key regulator of the receptor signaling activity. However, the molecular mechanisms underlying EGFR endocytosis are incompletely understood. Although ligand-induced ubiquitination of EGFR is known to promote its endocytic trafficking, the importance of EGFR ubiquitination in clathrin-mediated endocytosis, the primary physiological route of EGFR internalization, remains debated, and the relative contributions of ubiquitination-dependent and -independent mechanisms are not defined. Hence, we used NX-1013, a small-molecule inhibitor of the Casitas B-lineage lymphoma-b (CBLB) E3 ubiquitin ligase, to dissect the role of EGFR ubiquitination in its endocytic trafficking and signaling. Strikingly, brief treatment with NX-1013 completely abolished EGF-induced EGFR ubiquitination, demonstrating that this process is exclusively mediated by the closely related CBLB and CBL ligases. NX-1013 inhibited clathrin-mediated internalization of activated EGFR by 60 to 70%. The remaining, ubiquitination-independent internalization required EGFR kinase activity, was highly clathrin-dependent, and was significantly impaired by depletion of the AP-2 clathrin adaptor complex. Interestingly, inhibition of CBLs and EGFR endocytosis by NX-1013 did not affect major downstream signaling pathways in human oral squamous cell carcinoma cells, with the exception of Rac1 activation and EGFR-dependent cell migration, both of which were suppressed.
Structural insights into SetA-mediated Rab1 glucosylation and PI3P-guided localization during early <i>Legionella</i> infection
The bacterial pathogen Legionella pneumophila secretes effector proteins that remodel host endomembranes to establish a replication-permissive niche known as the Legionella -containing vacuole (LCV). Among these, SetA disrupts vesicle trafficking by glucosylating the small GTPase Rab1, essential for ER-to-Golgi transport. Here, we report comprehensive structural and mechanistic insights into SetA-mediated Rab1 glucosylation and its PI3P-dependent membrane targeting. Crystal structures of its N-terminal glycosyltransferase and C-terminal lipid-binding domains, captured in multiple ligand-bound states, reveal how SetA specifically recognizes GDP-bound Rab1 and the head group of phosphatidylinositol 3-phosphate (PI3P), which is enriched on early LCV membranes. SAXS-based full-length modeling, biochemical assays, and cellular imaging analyses demonstrate that SetA integrates Rab1 modification with membrane localization, thereby perturbing Golgi integrity and ER morphology. Together, these findings define the dual structural mechanisms underlying SetA’s coordination of substrate glucosylation and membrane association, providing a spatiotemporal framework for understanding Legionella ’s early infection strategy.