Patients with Alzheimer disease (AD) often experience neuropsychiatric symptoms, particularly anxious-depressive symptoms and sleep disturbances. These symptoms are associated with various factors related to AD, including amyloid-β and tau pathology, neurodegeneration, and cognitive decline, at different stages of the disease. However, it remains unclear whether anxious-depressive symptoms and sleep disturbances are merely symptoms or contribute as risk factors in the development and progression of AD. Consequently, there is a pressing need for a timely and informed discussion regarding these disturbances in AD. Here we discuss the most recent developments in understanding the etiology of anxious-depressive symptoms and sleep disturbances in AD, with a focus on how these symptoms interact with AD biomarkers to influence cognitive decline. Furthermore, we propose models of connections between anxious-depressive symptoms and/or sleep disturbances, AD biomarkers and cognition, aiming to inspire potential treatment plans for addressing these symptoms and exploring their impact on AD pathology and cognitive decline.

Perceptual decision-making is thought to be mediated by neuronal networks with attractor dynamics1,2. However, the dynamics underlying the complex neuronal responses during decision-making remain unclear. Here we use simultaneous recordings of hundreds of neurons, combined with an unsupervised, deep-learning-based method, to discover decision-related neural dynamics in the rat frontal cortex and striatum as animals accumulate pulsatile auditory evidence. We found that trajectories evolved along two sequential regimes: an initial phase dominated by sensory inputs, followed by a phase dominated by autonomous dynamics, with the flow direction (that is, neural mode) largely orthogonal to that in the first regime. We propose that this transition marks the moment of decision commitment, that is, the time when the animal makes up its mind. To test this, we developed a simplified model of the dynamics to estimate a putative neurally inferred time of commitment (nTc) for each trial. This model captures diverse single-neuron temporal profiles, such as ramping and stepping3,4. The estimated nTc values were not time locked to stimulus or response timing but instead varied broadly across trials. If nTc marks commitment, evidence before this point should affect the decision, whereas evidence afterwards should not. Behavioural analysis aligned to nTc confirmed this prediction. Our findings show that decision commitment involves a rapid, coordinated transition in dynamical regime and neural mode and suggest that nTc offers a useful neural marker for studying rapid changes in internal brain state.

Neuroendocrine and tuft cells are rare chemosensory epithelial lineages defined by the expression of ASCL1 and POU2F3 transcription factors, respectively. Neuroendocrine cancers, including small cell lung cancer (SCLC), frequently display tuft-like subsets, a feature linked to poor patient outcomes1-9. The mechanisms driving neuroendocrine-tuft tumour heterogeneity and the origins of tuft-like cancers are unknown. Using multiple genetically engineered animal models of SCLC, we demonstrate that a basal cell of origin (but not the accepted neuroendocrine origin) generates neuroendocrine-tuft-like tumours that highly recapitulate human SCLC. Single-cell clonal analyses of basal-derived SCLC further uncovered unexpected transcriptional states, including an Atoh1+ state, and lineage trajectories underlying neuroendocrine-tuft plasticity. Uniquely in basal cells, the introduction of genetic alterations enriched in human tuft-like SCLC, including high MYC, PTEN loss and ASCL1 suppression, cooperates to promote tuft-like tumours. Transcriptomics of 944 human SCLCs revealed a basal-like subset and a tuft-ionocyte-like state that altogether demonstrate notable conservation between cancer states and normal basal cell injury response mechanisms10-13. Together, these data indicate that the basal cell is a probable origin for SCLC and other neuroendocrine-tuft cancers that can explain neuroendocrine-tuft heterogeneity, offering new insights for targeting lineage plasticity.

Directly visualizing vibrational anisotropy in individual phonon modes is essential for understanding a wide range of intriguing optical, thermal and elastic phenomena in materials1-5. Although conventional optical and diffraction techniques have been used to estimate vibrational anisotropies, they fall short in achieving the spatial and energy resolution necessary to provide detailed information4-7. Here, we introduce a new form of momentum-selective electron energy-loss spectroscopy, which enables the element-resolved imaging of frequency- and symmetry-dependent vibrational anisotropies with atomic resolution. Vibrational anisotropies manifest in different norms of orthogonal atomic displacements, known as thermal ellipsoids. Using the centrosymmetric strontium titanate as a model system, we observed two distinct types of oxygen vibrations with contrasting anisotropies: oblate thermal ellipsoids below 60 meV and prolate ones above 60 meV. In non-centrosymmetric barium titanate, our approach can detect subtle distortions of the oxygen octahedra by observing the unexpected modulation of q-selective signals between apical and equatorial oxygen sites near 55 meV, which originates from reduced crystal symmetry and may also be linked to ferroelectric polarization. These observations are quantitatively supported by theoretical modelling, which demonstrates the reliability of our approach. The measured frequency-dependent vibrational anisotropies shed new light on the dielectric and thermal behaviours governed by acoustic and optical phonons. The ability to visualize phonon eigenvectors at specific crystallographic sites with unprecedented spatial and energy resolution opens new avenues for exploring dielectric, optical, thermal and superconducting properties.

As a negative charge carrier, the hydride ion (H-) is more energetic, polarizable and reactive than cations1. An H--mediated electrochemical process is fundamentally different from existing systems and enables the development of innovative electrochemical devices, such as rechargeable batteries, fuel cells, electrolysis cells and gas separation membranes2. Here we developed a core-shell hydride 3CeH3@BaH2, which exhibits fast H- conduction at ambient temperature and becomes a superionic conductor above 60 °C. This hydride allows us to construct an all-solid-state rechargeable H- battery CeH2|3CeH3@BaH2|NaAlH4, which operates at ambient conditions using NaAlH4 and CeH2 as cathode and anode materials, respectively. This battery has an initial specific capacity of 984 mAh g-1 and retains 402 mAh g-1 after 20 cycles. Using hydrogen as charge carriers can avoid the formation of detrimental metal dendrites, in principle, which creates new research avenues for clean energy storage and conversion.

The regulation of metabolic processes by proteins is fundamental to biology and yet is incompletely understood. Here we develop a mass spectrometry (MS)-based approach that leverages genetic diversity to nominate functional relationships between 285 metabolites and 11,868 proteins in living tissues. This method recapitulates protein-metabolite functional relationships mediated by direct physical interactions and local metabolic pathway regulation while nominating 3,542 previously undescribed relationships. With this foundation, we identify a mechanism of regulation over liver cysteine utilization and cholesterol handling, regulated by the poorly characterized protein LRRC58. We show that LRRC58 is the substrate adaptor of an E3 ubiquitin ligase that mediates proteasomal degradation of CDO1, the rate-limiting enzyme of the catabolic shunt of cysteine to taurine1. Cysteine abundance regulates LRRC58-mediated CDO1 degradation, and depletion of LRRC58 is sufficient to stabilize CDO1 to drive consumption of cysteine to produce taurine. Taurine has a central role in cholesterol handling, promoting its excretion from the liver2, and we show that depletion of LRRC58 in hepatocytes increases cysteine flux to taurine and lowers hepatic cholesterol in mice. Uncovering the mechanism of LRRC58 control over cysteine catabolism exemplifies the utility of covariation MS to identify modes of protein regulation of metabolic processes.

Repetitive head impacts (RHIs) sustained from contact sports are the largest risk factor for chronic traumatic encephalopathy (CTE)1-4. Currently, CTE can only be diagnosed after death and the events that trigger initial hyperphosphorylated tau (p-tau) deposition remain unclear2. Furthermore, the symptoms endorsed by young individuals are not fully explained by the extent of p-tau deposition2, severely hampering therapeutic interventions. Here we observed a multicellular response prior to the onset of CTE p-tau pathology that correlates with number of years of RHI exposure in young people (less than 51 years of age) with RHI exposure, the majority of whom played American football. Leveraging single-nucleus RNA sequencing of tissue from 8 control individuals, 9 RHI-exposed individuals and 11 individuals with low-stage CTE, we identify SPP1-expressing inflammatory microglia, angiogenic and inflamed endothelial cells, astrocytosis and altered synaptic gene expression in those exposed to RHI. We also observe a significant loss of cortical sulcus layer 2/3 neurons independent of p-tau pathology. Finally, we identify TGFβ1 as a potential signal that mediates microglia-endothelial cell cross talk. These results provide robust evidence that multiple years of RHI is sufficient to induce lasting cellular alterations that may underlie p-tau deposition and help explain the early pathogenesis in young former contact sport athletes. Furthermore, these data identify specific cellular responses to RHI that may direct future identification of diagnostic and therapeutic strategies for CTE.

Accretion disks in strong gravity ubiquitously produce winds, seen as blueshifted absorption lines in the X-ray band of both stellar mass X-ray binaries (black holes and neutron stars)1-4 and supermassive black holes5. Some of the most powerful winds (termed Eddington winds) are expected to arise from systems in which radiation pressure is sufficient to unbind material from the inner disk (L ≳ LEdd). These winds should be extremely fast and carry a large amount of kinetic power, which, when associated with supermassive black holes, would make them a prime contender for the feedback mechanism linking the growth of those black holes with their host galaxies6. Here we show the XRISM Resolve spectrum of the galactic neutron star X-ray binary, GX 13+1, which reveals one of the densest winds ever seen in absorption lines. This Compton-thick wind significantly attenuates the flux, making it appear faint, although it is intrinsically more luminous than usual (L ≳ LEdd). However, the wind is extremely slow, more consistent with the predictions of thermal-radiative winds launched by X-ray irradiation of the outer disk than with the expected Eddington wind driven by radiation pressure from the inner disk. This puts new constraints on the origin of winds from bright accretion flows in binaries, but also highlights the very different origin required for the ultrafast (v ~ 0.3c) winds seen in recent Resolve observations of a supermassive black hole at a similarly high Eddington ratio7.

With the rise of decentralized computing, such as in the Internet of Things, autonomous driving and personalized healthcare, it is increasingly important to process time-dependent signals 'at the edge' efficiently: right at the place where the temporal data are collected, avoiding time-consuming, insecure and costly communication with a centralized computing facility (or 'cloud'). However, modern-day processors often cannot meet the restrained power and time budgets of edge systems because of intrinsic limitations imposed by their architecture (von Neumann bottleneck) or domain conversions (analogue to digital and time to frequency). Here we propose an edge temporal-signal processor based on two in-materia computing systems for both feature extraction and classification, reaching near-software accuracy for the TI-46-Word1 and Google Speech Commands2 datasets. First, a nonlinear, room-temperature reconfigurable-nonlinear-processing-unit3,4 layer realizes analogue, time-domain feature extraction from the raw audio signals, similar to the human cochlea. Second, an analogue in-memory computing chip5, consisting of memristive crossbar arrays, implements a compact neural network trained on the extracted features for classification. With submillisecond latency, reconfigurable-nonlinear-processing-unit-based feature extraction consuming roughly 300 nJ per inference, and the analogue in-memory computing-based classifier using around 78 µJ (with potential for roughly 10 µJ)6, our findings offer a promising avenue for advancing the compactness, efficiency and performance of heterogeneous smart edge processors through in materia computing hardware.

The mechanistic target of rapamycin complex 1 (mTORC1) integrates growth factor (GF) and nutrient signals to stimulate anabolic processes connected to cell growth and inhibit catabolic processes such as autophagy1,2. GF signalling through the tuberous sclerosis complex regulates the lysosomally localized small GTPase RAS homologue enriched in brain (RHEB)3. Direct binding of RHEB-GTP to the mTOR kinase subunit of mTORC1 allosterically activates the kinase by inducing a large-scale conformational change4. Here we reconstituted mTORC1 activation on membranes by RHEB, RAGs and Ragulator. Cryo-electron microscopy showed that RAPTOR and mTOR interact directly with the membrane. Full engagement of the membrane anchors is required for optimal alignment of the catalytic residues in the mTOR kinase active site. Converging signals from GFs and nutrients drive mTORC1 recruitment to and activation on lysosomal membrane in a four-step process, consisting of (1) RAG-Ragulator-driven recruitment to within ~100 Å of the lysosomal membrane; (2) RHEB-driven recruitment to within ~40 Å; (3) RAPTOR-membrane engagement and intermediate enzyme activation; and (4) mTOR-membrane engagement and full enzyme activation. RHEB and membrane engagement combined leads to full catalytic activation and structurally explains GF and nutrient signal integration at the lysosome.

Prime editors make programmed genome modifications by writing new sequences into extensions of nicked DNA 3' ends1. These edited 3' new strands must displace competing 5' strands to install edits, yet a bias towards retaining the competing 5' strands hinders efficiency and can cause indel errors2. Here we discover that nicked end degradation, consistent with competing 5' strand destabilization, can be promoted by Cas9-nickase mutations that relax nick positioning. We exploit this mechanism to engineer efficient prime editors with strikingly low indel errors. Combining this error-suppressing strategy with the latest efficiency-boosting architecture, we design a next-generation prime editor (vPE). Compared with previous editors, vPE features comparable efficiency yet up to 60-fold lower indel errors, enabling edit:indel ratios as high as 543:1.

Decision-making in healthcare relies on understanding patients' past and current health states to predict and, ultimately, change their future course1-3. Artificial intelligence (AI) methods promise to aid this task by learning patterns of disease progression from large corpora of health records4,5. However, their potential has not been fully investigated at scale. Here we modify the GPT6 (generative pretrained transformer) architecture to model the progression and competing nature of human diseases. We train this model, Delphi-2M, on data from 0.4 million UK Biobank participants and validate it using external data from 1.9 million Danish individuals with no change in parameters. Delphi-2M predicts the rates of more than 1,000 diseases, conditional on each individual's past disease history, with accuracy comparable to that of existing single-disease models. Delphi-2M's generative nature also enables sampling of synthetic future health trajectories, providing meaningful estimates of potential disease burden for up to 20 years, and enabling the training of AI models that have never seen actual data. Explainable AI methods7 provide insights into Delphi-2M's predictions, revealing clusters of co-morbidities within and across disease chapters and their time-dependent consequences on future health, but also highlight biases learnt from training data. In summary, transformer-based models appear to be well suited for predictive and generative health-related tasks, are applicable to population-scale datasets and provide insights into temporal dependencies between disease events, potentially improving the understanding of personalized health risks and informing precision medicine approaches.

Controlling arms and legs requires feedback from the proprioceptive sensory neurons that detect joint position and movement1,2. Proprioceptive feedback must be tuned for different behavioural contexts3-6, but the underlying circuit mechanisms remain poorly understood. Here, using calcium imaging in behaving Drosophila, we find that the axons of position-encoding leg proprioceptors are active across a range of behaviours, whereas the axons of movement-encoding leg proprioceptors are suppressed during walking and grooming. Using connectomics7-9, we identify a specific class of interneurons that provide GABAergic presynaptic inhibition to the axons of movement-encoding proprioceptors. These interneurons receive input from parallel excitatory and inhibitory descending pathways that are positioned to drive the interneurons in a context-specific and leg-specific manner. Calcium imaging from both the interneurons and their descending inputs confirms that their activity is correlated with self-generated but not passive leg movements. Taken together, our findings reveal a neural circuit that suppresses specific proprioceptive feedback signals during self-generated movements.

Neutrophils, the most abundant and biotoxic immune cells, extrude nuclear DNA into the extracellular space to maintain homeostasis. Termed neutrophil extracellular traps (NETs), these protein-modified and decondensed extracellular DNA scaffolds control infection and are involved in coagulation, autoimmunity and cancer1,2. Here we show how myeloperoxidase (MPO), a highly expressed neutrophil protein, disassembles nucleosomes, thereby facilitating NET formation, yet also binds stably to NETs extracellularly. We describe how the oligomeric status of MPO governs both outcomes. MPO dimers interact with nucleosomal DNA using one protomer and concurrently dock into the nucleosome acidic patch with the other protomer. As a consequence, dimeric MPO displaces DNA from the core complex, culminating in nucleosome disassembly. On the other hand, MPO monomers stably interact with the nucleosome acidic patch without making concomitant DNA contacts, explaining how monomeric MPO binds to and licences NETs to confer hypohalous acid production in the extracellular space3. Our data demonstrate that the binding of MPO to chromatin is governed by specific molecular interactions that transform chromatin into a non-replicative, non-encoding state that offers new biological functions in a cell-free manner. We propose that MPO is, to our knowledge, the first member of a class of proteins that convert chromatin into an immune effector.

Hole-selective self-assembled monolayers (SAMs)1,2 have played a key role in driving the certified power conversion efficiency (PCE) of inverted perovskite solar cells3-5 to 26.7% (ref. 6). However, their instability often compromises the operational performance of devices, strongly hindering their practical applications7,8. Here we employ a cross-linkable co-SAM to enhance the conformational stability of hole-selective SAMs against external stresses, while suppressing the formation of defects and voids in SAM during self-assembly. The azide-containing SAM can be thermally activated to form a cross-linked and densely assembled co-SAM with a thermally stable conformation and preferred orientation. This effectively minimizes substrate surface exposure caused by wiggling of loose SAMs under thermal stress, preventing perovskite decomposition. This enables a certified PCE of 26.92% to be achieved for the best-performing cell, which also possesses excellent thermal stability with negligible decay under maximum-power-point tracking at 85 °C for 1,000 h. It also retains >98% of initial PCE after 700 repetitive thermal cycles between -40 °C and 85 °C, representing the state of the art of the field. This work offers an in-depth understanding of SAM degradation mechanisms to guide the design of a more robust buried interface for SAM-based devices adopting high-roughness substrates to realize highly efficient and durable perovskite solar cells.

Brown and beige adipocytes express uncoupling protein 1 (UCP1), a mitochondrial protein that dissociates respiration from ATP synthesis and promotes heat production and energy expenditure. However, UCP1-/- mice are not obese1-5, consistent with the existence of alternative mechanisms of thermogenesis6-8. Here we describe a UCP1-independent mechanism of thermogenesis involving ATP-consuming metabolism of monomethyl branched-chain fatty acids (mmBCFA) in peroxisomes. These fatty acids are synthesized by fatty acid synthase using precursors derived from catabolism of branched-chain amino acids9 and our results indicate that β-oxidation of mmBCFAs is mediated by the peroxisomal protein acyl-CoA oxidase 2 (ACOX2). Notably, cold exposure upregulated proteins involved in both biosynthesis and β-oxidation of mmBCFA in thermogenic fat. Acute thermogenic stimuli promoted translocation of fatty acid synthase to peroxisomes. Brown-adipose-tissue-specific fatty acid synthase knockout decreased cold tolerance. Adipose-specific ACOX2 knockout also impaired cold tolerance and promoted diet-induced obesity and insulin resistance. Conversely, ACOX2 overexpression in adipose tissue enhanced thermogenesis independently of UCP1 and improved metabolic homeostasis. Using a peroxisome-localized temperature sensor named Pexo-TEMP, we found that ACOX2-mediated fatty acid β-oxidation raised intracellular temperature in brown adipocytes. These results identify a previously unrecognized role for peroxisomes in adipose tissue thermogenesis characterized by an mmBCFA synthesis and catabolism cycle.

The fin-to-limb transition in vertebrate evolution has been central to the study of how development underlies evolutionary change. In this context, the functional analysis of Hox gene regulation to infer evolutionary trajectories has been critical to explain the origin of new features. In tetrapods, the transcription of Hoxd genes in developing digits depends on a set of enhancers forming a large regulatory landscape1,2. The presence of a syntenic counterpart in zebrafish, which lacks digits, suggests deep homology3 or shared developmental foundations underlying distal fin and limbs. However, how this regulatory program evolved has remained unresolved. We genetically evaluated the function of the zebrafish Hoxd regulatory landscapes by comparatively assessing the effects of their full deletions. We show that, unlike in mice, deletion of these regions in fish does not disrupt hoxd gene transcription during distal fin development. By contrast, we found that this deficiency leads to the loss of expression within the cloaca, a structure related by ancestry to the mammalian urogenital sinus, and that distal hox13 genes are essential for correct cloacal formation. Because Hoxd gene regulation in the mouse urogenital sinus relies on enhancers located in this same chromatin domain that controls digit development, we propose that the current regulatory landscape active in distal limbs was co-opted as a whole in tetrapods from a pre-existing cloacal regulatory machinery.

Most neurodevelopmental disorders with single gene diagnoses act via haploinsufficiency, in which only one of the two gene copies is functional1. SCN2A haploinsufficiency is one of the most frequent causes of neurodevelopmental disorder, often presenting with autism spectrum disorder, intellectual disability and, in a subset of children, refractory epilepsy2. Here, using SCN2A haploinsufficiency as a proof-of-concept, we show that upregulation of the existing functional gene copy through CRISPR activation (CRISPRa) can rescue neurological-associated phenotypes in Scn2a haploinsufficient mice. We first show that restoring Scn2a expression in adolescent heterozygous Scn2a conditional knock-in mice rescues electrophysiological deficits associated with Scn2a haploinsufficiency (Scn2a+/-). Next, using an adeno-associated virus CRISPRa-based treatment in adolescent mice, we show that we can correct intrinsic and synaptic deficits in neocortical pyramidal cells, a major cell type that contributes to neurodevelopmental disorders and seizure aetiology in SCN2A haploinsufficiency. Furthermore, we find that systemic delivery of CRISPRa protects Scn2a+/- mice against chemoconvulsant-induced seizures. Finally, we also show that adeno-associated virus CRISPRa treatment rescues excitability in SCN2A haploinsufficient human stem-cell-derived neurons. Our results showcase the potential of this therapeutic approach to rescue SCN2A haploinsufficiency and demonstrates that rescue even at adolescent stages can ameliorate neurodevelopmental phenotypes.

The dome-headed pachycephalosaurians are among the most enigmatic dinosaurs. Bearing a hypertrophied skull roof and elaborate cranial ornamentation, members of the clade are considered to have evolved complex sociosexual systems1-3. Despite their importance in understanding behavioural ecology in Dinosauria, the absence of uncontested early diverging taxa has hindered our ability to reconstruct the origin and early evolution of the clade4-7. Here we describe Zavacephale rinpoche gen. et sp. nov., from the Lower Cretaceous Khuren Dukh Formation of Mongolia, the most skeletally complete and geologically oldest pachycephalosaurian discovered globally. Z. rinpoche exhibits a well-developed frontoparietal dome and preserves the clade's first record of manual elements and gastroliths. Phylogenetic analysis recovered Z. rinpoche as one of the earliest diverging pachycephalosaurians, pushing back fossil evidence of the frontoparietal dome by at least 14 Myr and clarifying macroevolutionary trends in its assembly. We found that the earliest stage of dome evolution occurred by means of a frontal-first developmental pattern with retention of open supratemporal fenestra, mirroring proposed ontogenetic trajectories in some Late Cretaceous taxa. Finally, intraskeletal osteohistology of the frontoparietal dome and hindlimb demonstrate decoupling of sociosexual and somatic maturity in early pachycephalosaurians, with advanced dome development preceding terminal body size.

Although artificial intelligence enables productivity gains from delegating tasks to machines1, it may facilitate the delegation of unethical behaviour2. This risk is highly relevant amid the rapid rise of 'agentic' artificial intelligence systems3,4. Here we demonstrate this risk by having human principals instruct machine agents to perform tasks with incentives to cheat. Requests for cheating increased when principals could induce machine dishonesty without telling the machine precisely what to do, through supervised learning or high-level goal setting. These effects held whether delegation was voluntary or mandatory. We also examined delegation via natural language to large language models5. Although the cheating requests by principals were not always higher for machine agents than for human agents, compliance diverged sharply: machines were far more likely than human agents to carry out fully unethical instructions. This compliance could be curbed, but usually not eliminated, with the injection of prohibitive, task-specific guardrails. Our results highlight ethical risks in the context of increasingly accessible and powerful machine delegation, and suggest design and policy strategies to mitigate them.